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Кластеризация в ML: от теоретических основ популярных алгоритмов к их реализации с нуля на Python

Кластеризация — это набор методов без учителя для группировки данных по определённым критериям в так называемые кластеры, что позволяет выявлять сходства и различия между объектами, а также упрощать их анализ и визуализацию. Из-за частичного сходства в постановке задач с классификацией кластеризацию ещё называют unsupervised classification.

В данной статье описан не только принцип работы популярных алгоритмов кластеризации от простых к более продвинутым, но а также представлены их упрощённые реализации с нуля на Python, отражающие основную идею. Помимо этого, в конце каждого раздела указаны дополнительные источники для более глубокого ознакомления.

Ноутбук с данными алгоритмами можно загрузить на Kaggle (eng) и GitHub (rus).

Содержание

Области применения кластеризации и её разновидности
К-средних
Агломеративная кластеризация
Спектральная кластеризация
DBSCAN
Affinity Propagation

Области применения кластеризации и её разновидности

Кластеризация широко применяется в машинном обучении для решения различного спектра задач:

классификация (определение к какому классу относится каждый объект или же выделение новых классов, которые не были известны заранее);
сегментация рынка (разделение потенциальных клиентов на группы по их характеристикам для разработки более эффективных стратегий в маркетинге и продажах);
сегментация изображений (разделение изображения на сегменты или группы пикселей);
кластеризация геоданных (группировка данных по их географическому расположению, например, разделение районов на безопасные и опасные, богатые и бедные, и так далее);
понижение размерности (уменьшение количества признаков путем объединения схожих в один кластер).

Существует множество различных типов кластеризации, которые можно разделить по следующим критериям:

По способу формирования кластеров:
- Разделительные (partitioning) — разбивают данные на заданное число кластеров, минимизируя расстояние внутри кластера и максимизируя расстояние между кластерами (например, K-means).
- Основанные на плотности (density-based) — группируют точки, которые находятся в областях с высокой плотностью и отделяют их от областей с низкой плотностью (например, DBSCAN).
- Основанные на сетке (grid-based) — разбивают пространство на ячейки сетки и анализируют плотность данных в каждой ячейке (например, STING).
- Основанные на модели (model-based) — предполагают, что данные порождены некоторой статистической моделью и пытаются подобрать параметры этой модели (например, смеси Гауссианов).
- Основанные на графах (graph-based) — используют графовое представление данных и разбивают его на подграфы, соответствующие кластерам (например, спектральная кластеризация).
- Основанные на подпространствах (subspace-based) — ищут кластеры в подпространствах признаков, а не во всём пространстве (например, CLIQUE).
- Основанные на ансамбле (ensemble-based) — комбинируют результаты различных алгоритмов кластеризации, чтобы получить более стабильное и надежное разбиение (например, CSPA).
По степени вложенности кластеров:
- Плоские (flat) — разбивают данные на один уровень кластеров, не учитывая их иерархию (например, K-means).
- Иерархические (hierarchical) — разбивают данные на несколько уровней кластеров, учитывая их иерархию. Существуют два основных подхода к иерархической кластеризации: агломеративный (начинается с того, что каждый объект является отдельным кластером, а затем постепенно наиболее близкие кластеры объединяются в более крупные) и дивизивный (начинается с того, что все объекты составляют один кластер, а затем постепенно разделяются на более мелкие кластеры).
По степени пересечения кластеров:
- Исключающие (exclusive) — каждый объект принадлежит только одному кластеру (например, K-means).
- Перекрывающие (overlapping) — каждый объект может принадлежать нескольким кластерам (например, MCOKE).
- Нечёткие (fuzzy) — каждый объект принадлежит каждому кластеру с некоторой степенью принадлежности (например, fuzzy K-means).

Алгоритмы кластеризации в scikit-learn

Далее более подробно будут рассмотрены наиболее популярные алгоритмы кластеризации, представляющие наибольший интерес с практической точки зрения.

K-Means

Кластеризация K-средних представляет собой одну из самых простых реализаций, суть которой заключается в итеративной инициализации центроидов для каждого кластера на основе среднего арифметического расположенных в нём наблюдений, а также их переопределении путём минимизации суммарного квадратичного отклонения от центроидов кластеров.

Схема кластеризации K-средних

Существуют различные вариации алгоритма K-Means, которые модифицируют его шаги или функцию потерь для улучшения производительности, а также применимости к разным типам данных. К самым популярным вариациям относятся следующие:

Lloyd's algorithm — это классический вариант K-Means, который хорошо работает для сферических кластеров с одинаковой плотностью, но может давать плохие результаты для других форм или размеров кластеров.
Elkan algorithm — более быстрый вариант классического K-Means, который использует неравенство треугольника для уменьшения количества вычислений расстояний между объектами и центроидами, что может быть эффективнее на некоторых наборах данных с хорошо определенными кластерами, однако требуется больше памяти из-за выделения дополнительного массива размера (n_samples, n_clusters).
Mini-batch K-Means — модификация классического K-Means, использующая случайные подвыборки данных на каждой итерации для обучения. Хорошо подходит для больших датасетов.
K-Medoids — вариант K-Means, который в качестве центроидов выбирает реальные точки (медоиды) из данных, а не их средние значения, что повышает устойчивость к выбросам.
K-Modes — вариант алгоритма K-Means для работы с категориальными данными, который выбирает один из объектов в кластере в качестве моды и минимизирует сумму расстояний Хэмминга между модой и объектами в кластере. Расстояние Хэмминга представляет из себя количество позиций, в которых значения векторов не совпадают.

Одним из ключевых вопросов при использовании K-Means является выбор начальных центроидов, поскольку от них зависит качество и скорость сходимости алгоритма. Существует несколько способов инициализации центроидов:

Случайный выбор: выбирается k случайных точек из данных в качестве начальных центроидов. Такой метод прост, но может привести к плохим результатам, если начальные центроиды слишком близки друг к другу или к краям распределения.
K-Means++: первый центроид выбирается случайно, а затем выбираются остальные центроиды с вероятностью, пропорциональной квадрату расстояния до ближайшего уже выбранного центроида. Данный метод улучшает качество кластеризации, уменьшая вероятность попадания в локальный минимум, но требует дополнительных вычислений.
Greedy K-Means++ — модификация K-Means++, которая ускоряет сходимость и улучшает качество кластеризации за счёт того, что на каждом шаге при выборе центра кластера производится несколько попыток и выбирается лучший (тот, который минимизирует суммарное квадратичное отклонение точек от центров кластеров).

Другим важным аспектом, влияющим на качество алгоритма, является подбор оптимального числа кластеров k, которое устанавливается заранее вручную. Существует несколько методов для выбора оптимального k:

Метод локтя, основанный на графике суммы квадратов расстояний между объектами и центроидами кластеров (SSE) в зависимости от k. Оптимальным k считается та точка, после которой SSE уменьшается незначительно.
Метод силуэта, основанный на графике среднего значения силуэта для каждого k. Силуэт — это мера того, насколько хорошо объект отнесен к своему кластеру по сравнению с другими кластерами. Оптимальным k считается та точка, где силуэт достигает максимума.
Метод комплексной оценки, основанный на анализе нескольких критериев, таких как динамика перераспределения объектов в кластерах, изменение потенциальной энергии объектов внутри кластеров и характерные точки графиков этих критериев. Оптимальным k считается точка, которая удовлетворяет набору правил, использующих данные критерии.

Принцип работы Lloyd's K-Means с инициализацией Greedy K-Means++

Алгоритм строится следующим образом:

1) изначально вычисляются центроиды кластеров с помощью алгоритма Greedy K-Means++;
2) далее рассчитывается квадрат евклидова (или другого) расстояния от каждого наблюдения до центроидов;
3) на основе полученного расстояния наблюдениям присваиваются метки кластеров, которые к ним расположены ближе всего, а также рассчитывается инерция — мера того, насколько хорошо данные были разбиты на кластеры;
4) шаги 2-3 повторяются до тех пор, пока инерция на текущей и предыдущей итерациях перестанет изменяться меньше установленного порога (пока положение центроидов перестанет изменяться в пространстве) или пока не будет достигнуто установленное количество итераций;
5) Наблюдения, расположенные ближе всего к полученным центроидам, и будут составлять кластеры.

Принцип работы алгоритма Greedy K-Means++:

1) первый центроид выбирается случайным образом из данных;
2) для каждого следующего центроида выбирается точка в данных с вероятностью, пропорциональной квадрату расстояния до ближайшего центроида среди нескольких кандидатов, выбранных случайным образом;
3) данный процесс повторяется пока не будет выбрано установленное количество центроидов.

Импорт необходимых библиотек

import numpy as np
from scipy.spatial.distance import cdist
import matplotlib.pyplot as plt
from sklearn.datasets import make_blobs
from sklearn.metrics import adjusted_rand_score
from sklearn.cluster import KMeans

Реализация на Python с нуля

class KMeansClustering:
    def __init__(self, n_clusters=8, max_iter=300, tol=0.0001, random_state=0):
        self.n_clusters = n_clusters
        self.max_iter = max_iter
        self.tol = tol
        self.random_state = random_state

    def _greedy_kmeans_plus_plus(self, X):
        np.random.seed(self.random_state)
        n_samples, n_features = X.shape
        n_local_trials = 2 + int(np.log(self.n_clusters))

        indices = np.arange(n_samples)
        first_index = np.random.choice(indices)
        centers = np.zeros((self.n_clusters, n_features))

        centers[0] = X[first_index]
        first_center = centers[0].reshape(1, -1)
        sq_distances = cdist(X, first_center, metric='sqeuclidean').ravel()

        for i in range(1, self.n_clusters):
            min_cost = np.inf
            min_new_sq_distances = []
            best_candidate_index = None

            for _ in range(n_local_trials):
                candidates_probas = sq_distances / np.sum(sq_distances)
                candidate_index = np.random.choice(indices, p=candidates_probas)
                candidate = X[candidate_index].reshape(1, -1)

                new_sq_distances = cdist(X, candidate, metric='sqeuclidean').ravel()
                new_cost = np.sum(np.minimum(sq_distances, new_sq_distances))

                if new_cost < min_cost:
                    best_candidate_index = candidate_index
                    min_new_sq_distances = new_sq_distances
                    min_cost = new_cost

            centers[i] = X[best_candidate_index]   # Choose the new center
            sq_distances = np.minimum(sq_distances, min_new_sq_distances)

        return centers

    def fit(self, X):
        n_samples, n_features = X.shape
        self.inertia_ = np.inf
        self.cluster_centers_ = self._greedy_kmeans_plus_plus(X)

        # Lloyd's algorithm
        for _ in range(self.max_iter):
            distances = cdist(X, self.cluster_centers_, metric='sqeuclidean')
            labels = np.argmin(distances, axis=1)
            new_inertia = np.sum(np.min(distances, axis=1))
            new_centers = np.zeros((self.n_clusters, n_features))

            for k in range(self.n_clusters):
                new_centers[k] = np.mean(X[labels == k], axis=0)

            if np.abs(new_inertia - self.inertia_) < self.tol:
                break

            self.inertia_ = new_inertia
            self.cluster_centers_ = new_centers

    def predict(self, X):
        distances = cdist(X, self.cluster_centers_, metric='sqeuclidean')
        predicted_labels = np.argmin(distances, axis=1)

        return predicted_labels

Загрузка датасета

X1, y1 = make_blobs(n_samples=250, n_features=2, centers=8, random_state=0)
print(y1)


[1 3 7 7 6 7 1 3 7 7 0 3 1 1 3 3 5 1 7 4 0 1 1 3 4 7 0 0 6 7 0 0 5 5 7 2 1
 1 6 5 4 7 1 2 1 1 4 3 6 4 7 3 0 2 2 1 7 2 4 0 0 0 1 4 6 5 0 4 6 6 4 4 1 4
 2 3 1 1 5 4 6 4 1 2 5 0 7 6 7 3 0 1 2 5 1 5 3 3 3 1 5 4 0 4 7 6 2 2 2 4 6
 2 5 1 6 4 0 6 5 0 0 6 3 5 1 6 0 2 5 5 6 3 3 1 5 4 5 0 2 2 3 0 4 7 5 4 2 0
 2 6 2 5 2 1 4 1 5 0 4 6 7 5 5 7 6 2 2 3 6 1 7 3 4 7 2 6 6 4 2 2 0 5 4 4 6
 3 1 7 6 7 7 0 4 5 7 2 6 6 2 5 3 3 2 7 1 7 6 6 4 3 5 7 6 3 5 0 3 3 5 5 2 0
 6 3 4 0 5 3 5 2 0 6 4 0 1 1 2 2 0 1 3 7 0 7 0 3 4 7 3 7]

Обучение моделей и оценка полученных результатов

Как можно заметить, K-Means дал достаточно хорошую, но не идеальную кластеризацию данных, что обусловлено наличием небольшого числа выбросов и более сложной формой некоторых кластеров, чем сферическая.

KMeans

kmeans = KMeansClustering(n_clusters=8, random_state=0)
kmeans.fit(X1)
kmeans_pred_res = kmeans.predict(X1)
kmeans_ari = adjusted_rand_score(y1, kmeans_pred_res)
kmeans_centroinds = kmeans.cluster_centers_
print(f'Adjusted Rand Score for KMeans: {kmeans_ari}', '', sep='\n')
print('centroids', kmeans_centroinds, '', sep='\n')
print('prediction', kmeans_pred_res, sep='\n')


Adjusted Rand Score for KMeans: 0.8082423809657193

centroids
[[ 9.20217726 -2.23709633]
 [-1.5438023   7.64224793]
 [-8.61527648 -8.32916569]
 [ 0.81231976  4.02302811]
 [-1.81106448  2.87987747]
 [ 2.3666746   1.30457024]
 [ 1.47433518  8.49698324]
 [ 5.86512606  0.19818122]]

prediction
[5 1 2 2 6 2 5 1 2 2 5 1 5 5 1 1 5 5 2 0 3 7 3 1 0 2 3 3 6 2 1 3 7 7 2 4 5
 5 6 7 0 2 5 4 5 5 0 1 6 7 2 1 3 3 4 5 2 4 0 3 3 3 5 0 6 7 3 0 6 6 0 0 5 0
 3 1 5 5 7 0 3 0 5 4 7 3 2 6 2 6 3 5 4 5 5 7 1 1 1 3 7 0 3 0 2 6 3 4 4 0 6
 4 7 5 1 0 3 6 7 3 3 6 1 7 5 6 3 4 7 7 6 1 1 5 7 0 7 3 4 4 1 3 0 2 7 0 4 3
 4 6 4 7 4 5 0 5 7 3 0 6 2 7 5 2 6 4 3 3 6 5 2 1 0 2 4 6 6 0 4 4 3 7 0 0 6
 1 5 2 6 2 2 3 0 7 2 4 6 6 4 7 1 1 4 2 5 2 6 1 0 1 5 2 6 6 7 3 1 1 7 7 4 3
 6 1 0 3 7 1 7 4 4 6 0 3 5 5 4 4 3 3 1 2 3 2 3 1 0 2 1 2]

KMeans (scikit-learn)

sk_kmeans = KMeans(n_clusters=8, n_init='auto', random_state=0)
sk_kmeans.fit(X1)
sk_kmeans_pred_res = sk_kmeans.predict(X1)
sk_kmeans_ari = adjusted_rand_score(y1, sk_kmeans_pred_res)
sk_kmeans_centroinds = sk_kmeans.cluster_centers_
print(f'Adjusted Rand Score for sk KMeans: {sk_kmeans_ari}', '', sep='\n')
print(sk_kmeans_centroinds, '', sep='\n')
print('prediction', sk_kmeans_pred_res, sep='\n')


Adjusted Rand Score for sk KMeans: 0.8082423809657193

[[ 9.20217726 -2.23709633]
 [-1.5438023   7.64224793]
 [-8.61527648 -8.32916569]
 [ 0.81231976  4.02302811]
 [-1.81106448  2.87987747]
 [ 2.3666746   1.30457024]
 [ 1.47433518  8.49698324]
 [ 5.86512606  0.19818122]]

prediction
[5 1 2 2 6 2 5 1 2 2 5 1 5 5 1 1 5 5 2 0 3 7 3 1 0 2 3 3 6 2 1 3 7 7 2 4 5
 5 6 7 0 2 5 4 5 5 0 1 6 7 2 1 3 3 4 5 2 4 0 3 3 3 5 0 6 7 3 0 6 6 0 0 5 0
 3 1 5 5 7 0 3 0 5 4 7 3 2 6 2 6 3 5 4 5 5 7 1 1 1 3 7 0 3 0 2 6 3 4 4 0 6
 4 7 5 1 0 3 6 7 3 3 6 1 7 5 6 3 4 7 7 6 1 1 5 7 0 7 3 4 4 1 3 0 2 7 0 4 3
 4 6 4 7 4 5 0 5 7 3 0 6 2 7 5 2 6 4 3 3 6 5 2 1 0 2 4 6 6 0 4 4 3 7 0 0 6
 1 5 2 6 2 2 3 0 7 2 4 6 6 4 7 1 1 4 2 5 2 6 1 0 1 5 2 6 6 7 3 1 1 7 7 4 3
 6 1 0 3 7 1 7 4 4 6 0 3 5 5 4 4 3 3 1 2 3 2 3 1 0 2 1 2]

Визуализация прогнозов

plt.figure(figsize=(12, 5))

plt.subplot(1, 2, 1)
plt.subplots_adjust(wspace=0.2)
plt.scatter(X1[:, 0], X1[:, 1], c=kmeans_pred_res, cmap="rainbow")
plt.scatter(kmeans_centroinds[:, 0], kmeans_centroinds[:, 1], marker="x", color="black", s=100)
plt.title("KMeans")
plt.xlabel("Feature 1")
plt.ylabel("Feature 2")

plt.subplot(1, 2, 2)
plt.subplots_adjust(wspace=0.2)
plt.scatter(X1[:, 0], X1[:, 1], c=sk_kmeans_pred_res, cmap="rainbow")
plt.scatter(sk_kmeans_centroinds[:, 0], sk_kmeans_centroinds[:, 1], marker="x", color="black", s=100)
plt.title("KMeans (scikit-learn)")
plt.xlabel("Feature 1")

plt.show()

Ручная реализация vs scikit-learn

Преимущества и недостатки K-Means

Преимущества:

прост в реализации и понимании;
наличие большого числа модификаций;
высокая скорость работы и точность на данных сферической формы.

Недостатки:

низкая точность на данных с несферической формой кластеров;
чувствительность к начальным значениям центроидов и выбросам;
необходимость заранее устанавливать число кластеров, что может быть сложно или не оптимально.

Дополнительные источники

Статья «Improved Guarantees for k-means++ and k-means++ Parallel», Konstantin Makarychev, Aravind Reddy and Liren Shan.

Документация: описание K-Means, K-Means (алгоритм).

Видео: один, два.

Агломеративная кластеризация

Алгломеративная кластеризация — это метод иерархической кластеризации, который объединяет объекты в кластеры на основе их близости. Процесс кластеризации начинается с того, что изначально каждый объект считается отдельным кластером, а затем на каждом шаге два наиболее близких кластера сливаются в один, пока не будет достигнуто желаемое число кластеров или один общий кластер.

Важным аспектом в алгломеративной кластеризаци является способ вычисления расстояния между кластерами, который называется связью. Можно выделить несколько методов для вычисления связи:

Метод одиночной связи (single linkage): расстояние между кластерами равно минимальному расстоянию между точками из разных кластеров. Этот метод склонен к созданию длинных и извилистых кластеров.

$d_{\min}(C_i, C_j) = \min_{x \in C_i, y \in C_j} \rho(x, y)$

Метод полной связи (complete linkage): расстояние между кластерами равно максимальному расстоянию между точками из разных кластеров. Этот метод склонен к созданию компактных и сферических кластеров.

$d_{\max}(C_i, C_j) = \max_{x \in C_i, y \in C_j} \rho(x, y)$

Метод средней связи (average linkage): расстояние между кластерами равно среднему расстоянию между всеми парами точек из разных кластеров. Этот метод является компромиссом между методами одиночной и полной связи.

$d_{\text{avg}}(C_i, C_j) = \frac{1}{n_i n_j} \sum_{x \in C_i} \sum_{y \in C_j} \rho(x, y)$

Метод Уорда (Ward's linkage): расстояние между кластерами равно приросту суммы квадратов расстояний от точек до центроидов кластеров при объединении этих кластеров. Этот метод стремится минимизировать внутрикластерную дисперсию.

$d_{\text{ward}}(C_i, C_j) = \frac{n_i n_j}{n_i + n_j} \rho^2(\bar{x}_i, \bar{x}_j)$

Принцип работы агломеративной кластеризации на основе метода Уорда

Алгоритм строится следующим образом:

1) для каждой пары кластеров рассчитывается расстояние Уорда на основе евклидова расстояния;
2) метки с минимальным расстоянием, то есть ближайшие кластеры объединяются в новый следующим образом: всем объектам одного кластера присваиваются метки другого, после чего все новые метки, которые больше меток другого кластера, уменьшаются на 1, то есть их нумерация сдвигается влево для устранения пропусков в последовательности;
3) шаги 1-2 повторяются пока количество кластеров больше целевого n_clusters.

Импорт необходимых библиотек

import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial.distance import sqeuclidean
from scipy.cluster.hierarchy import linkage, dendrogram
from sklearn.datasets import make_blobs
from sklearn.metrics import adjusted_rand_score
from sklearn.cluster import AgglomerativeClustering

Реализация на Python с нуля

class HierarchicalAgglomerativeClustering:
    def __init__(self, n_clusters=2):
        self.n_clusters = n_clusters

    @staticmethod
    def _ward_distance(c1, c2):
        n1, n2 = len(c1), len(c2)
        c1_mean, c2_mean = np.mean(c1, axis=0), np.mean(c2, axis=0)
        sqeuclidean_dist = sqeuclidean(c1_mean, c2_mean)

        return (n1 * n2) / (n1 + n2) * sqeuclidean_dist

    @staticmethod
    def _update_labels(labels, min_cdist_idxs):
        # assign a cluster number to labels
        labels[labels == min_cdist_idxs[1]] = min_cdist_idxs[0]
        labels[labels > min_cdist_idxs[1]] -= 1

        return labels

    def fit_predict(self, X):
        labels = np.arange(len(X))
        clusters = [[x] for x in X]

        while len(clusters) > self.n_clusters:
            min_cdist, min_cdist_idxs = np.inf, []

            for i in range(len(clusters) - 1):
                for j in range(i + 1, len(clusters)):
                    cdist = self._ward_distance(clusters[i], clusters[j])

                    if cdist < min_cdist:
                        min_cdist = cdist
                        min_cdist_idxs = (i, j)

            labels = self._update_labels(labels, min_cdist_idxs)
            clusters[min_cdist_idxs[0]].extend(clusters.pop(min_cdist_idxs[1]))

        return np.array(labels)

Загрузка датасета

X2, y2 = make_blobs(n_samples=75, n_features=2, centers=5, random_state=0)
print(y2)


[0 3 4 3 2 4 0 2 0 4 2 4 2 2 0 0 0 3 2 0 2 2 2 3 4 1 1 2 3 0 4 4 3 3 3 2 2
 0 1 1 3 1 0 2 4 1 4 4 0 4 1 0 3 0 4 1 2 1 4 3 1 1 3 0 3 4 1 2 1 4 0 3 1 1
 3]

Обучение моделей и оценка полученных результатов

В данном случае агломеративная кластеризация также справилась достаточно хорошо, но при сравнении графиков можно заметить, что метки ручной реализации имеют другие значения и соответственно цвет на графике. Это связано с другим порядком формирования кластеров: в scikit-learn используется структура данных, известная как linkage tree, позволяющая визуализировать иерархию кластеров с помощью древовидной диаграммы (дендограммы), что может быть полезно при выборе оптимального количества кластеров.

Стоит отметить, что порядок формирования кластеров не влияет на качество кластеризации, поскольку сами метки кластеров разделяются правильно, что видно из одинаковых значений ARI.

AgglomerativeClustering

ac = HierarchicalAgglomerativeClustering(n_clusters=5)
ac_pred_res = ac.fit_predict(X2)
ac_ari = adjusted_rand_score(y2, ac_pred_res)
print(f'Adjusted Rand Score for AgglomerativeClustering: {ac_ari}', '', sep='\n')
print('prediction', ac_pred_res, sep='\n')


Adjusted Rand Score for AgglomerativeClustering: 0.8370870157432925

prediction
[0 1 2 0 3 2 0 3 0 2 3 2 3 3 0 0 0 1 3 0 3 3 0 1 2 4 4 3 1 3 2 2 1 1 1 3 3
 0 4 4 1 4 0 3 2 4 2 2 3 2 4 0 1 0 2 4 3 4 2 1 4 4 1 0 1 2 4 3 3 2 0 1 4 4
 1]

AgglomerativeClustering (scikit-learn)

sk_ac = AgglomerativeClustering(n_clusters=5, linkage='ward')
sk_ac_pred_res = sk_ac.fit_predict(X2)
sk_ac_ari = adjusted_rand_score(y2, sk_ac_pred_res)
print(f'Adjusted Rand Score for sk AgglomerativeClustering: {sk_ac_ari}', '', sep='\n')
print('prediction', sk_ac_pred_res, sep='\n')


Adjusted Rand Score for sk AgglomerativeClustering: 0.8370870157432925

prediction
[4 2 1 4 0 1 4 0 4 1 0 1 0 0 4 4 4 2 0 4 0 0 4 2 1 3 3 0 2 0 1 1 2 2 2 0 0
 4 3 3 2 3 4 0 1 3 1 1 0 1 3 4 2 4 1 3 0 3 1 2 3 3 2 4 2 1 3 0 0 1 4 2 3 3
 2]

Визуализация прогнозов

plt.figure(figsize=(12, 5))

plt.subplot(1, 2, 1)
plt.scatter(X2[:, 0], X2[:, 1], c=ac_pred_res, cmap='rainbow')
plt.title('AgglomerativeClustering')
plt.xlabel("Feature 1")
plt.ylabel("Feature 2")

plt.subplot(1, 2, 2)
plt.scatter(X2[:, 0], X2[:, 1], c=sk_ac_pred_res, cmap='rainbow')
plt.title('AgglomerativeClustering (scikit-learn)')
plt.xlabel("Feature 1")

plt.show()

Ручная реализация vs scikit-learn

linkage_matrix = linkage(X2, method='ward', metric='euclidean')

plt.figure(figsize=(10, 6))
dendrogram(linkage_matrix, color_threshold=10)
plt.xlabel("Sample Index")
plt.ylabel("Distance")
plt.title("Dendrogram")
plt.show()

Преимущества и недостатки аглометративной кластеризации

Преимущества:

адаптация к различным ситуациям и способность обнаружения кластеров произвольной формы;
возможность формирования информативной иерархии кластеров, которая позволяет выбирать оптимальное число кластеров или лучше изучать структуру данных.

Недостатки:

использование большого количества вычислительных ресурсов и памяти из-за работы со всей матрицей расстояний между объектами;
чувствительность к выбору критерия объединения кластеров, а также неустойчивость к шуму и выбросам, что может сильно искажать иерархию кластеров.

Дополнительные источники

Статья «Modern hierarchical, agglomerative clustering algorithms», Daniel Müllner.

Документация: описание AgglomerativeClustering, AgglomerativeClustering (алгоритм).

Видео: один, два, три.

Спектральная кластеризация

Спектральная кластеризация — метод кластеризации на основе спектральных свойств матрицы сходства графа, который представляет собой набор точек данных, связанных друг с другом в зависимости от их сходства. Основная идея заключается в преобразовании матрицы сходства графа в лаплассиан для получения его собственных векторов, которые в дальнейшем используются для проекции данных в новое пространство более низкой размерности для лучшей разделимости, где затем применяется другой метод кластеризации, например, такой как K-средних.

Существуют различные способы построения матрицы сходства, среди которых наиболее популярными являются следующие:

nearest_neighbors (путем вычисления графа ближайших соседей);
rbf (с использованием радиальной базисной функции);
предварительно вычисленные, где признаки представлены как матрица сходства или граф ближайших соседей;
различные ядра: xi-квадрат, линейное, полиномиальное, сигмоидальное и другие.

Также существуют различные стратегии разложения лаплассиана на собственные вектора и значения:

ARPACK (ARnoldi PACKage) — это программный пакет на языке Fortran, который реализует итерационный метод Арнольди для нахождения нескольких собственных значений и собственных векторов большой разреженной матрицы. Метод Арнольди — это обобщение метода Ланцоша, который строит ортогональный базис подпространства Крылова, порождённого матрицей и начальным вектором, а затем проецирует исходную собственную задачу на это подпространство.
LOBPCG (Locally Optimal Block Preconditioned Conjugate Gradient) — это метод, который реализует локально оптимальный, блочный, предобусловленный, сопряжённый градиент для нахождения нескольких наименьших по модулю собственных значений и собственных векторов большой положительно определенной матрицы. Основная идея LOBPCG заключается в том, что на каждой итерации он выбирает следующее приближение к собственному вектору так, чтобы минимизировать квадратичную форму, связанную с собственной задачей на трехмерном подпространстве, порождённом текущим приближением, предобусловленным остатком и последним обновлением. Это делается с помощью метода Релея-Ритца, который находит оптимальные линейные комбинации этих векторов.
AMG (Algebraic Multigrid methods) — это класс алгоритмов для решения больших систем уравнений, возникающих при дискретизации дифференциальных уравнений. В контексте кластеризации AMG методы уменьшают размер матрицы, переводя её на грубую сетку, где она имеет меньше элементов, но сохраняет свои свойства. Это делается с помощью двух операций: сглаживания и коррекции. Сглаживание — это простой итерационный метод, который уменьшает ошибку в приближённом решении собственной задачи. Коррекция — это переход на грубую сетку, где решается упрощённая собственная задача, а затем возвращается на тонкую сетку для корректировки решения. Этот процесс повторяется несколько раз, пока не будет достигнута нужная точность.

Стоит отметить, что последние 2 метода являются более быстрыми, но менее стабильными.

Принцип работы спектральной кластеризации ARPACK с RBF ядром

Алгоритм строится следующим образом:

1) на основе матрицы сходства графа строится его нормализованный лаплассиан $L = I - D^{-\frac{1}{2}}$ и диагональная матрица степеней вершин графа, где — единичная матрица;
2) далее с помощью алгоритма ARPACK вычисляются k-собственных векторов лаплассиана с указанием сдвига для ускорения вычислений (sigma), случайного вектора (v0), а также наибольших по модулю собственных значений (which="LM") так как они будут расположены ближе всего к сдвигу, что в конечном счёте вернёт наименьшие собственные вектора;
3) полученные вектора нормализуются по степеням вершин графа, чтобы быть независимыми от весов вершин, после чего в даннных векторах изменяется знак, чтобы стать детерменированными (такой подход позволяет избежать неоднозначности в знаках собственных векторов при использовании различных реализаций алгоритма);
4) из модифицированных собственных векторов формируется матрица вложения, к которой применяется алгоритм K-Means, который спрогнозирует в конечном счёте итоговые метки.

Импорт необходимых библиотек

import numpy as np
import matplotlib.pyplot as plt
from scipy.sparse.linalg import eigsh
from scipy.sparse.csgraph import laplacian as csgraph_laplacian
from sklearn.datasets import make_moons
from sklearn.preprocessing import StandardScaler
from sklearn.cluster import KMeans, SpectralClustering
from sklearn.metrics.pairwise import rbf_kernel
from sklearn.metrics.cluster import adjusted_rand_score

Реализация на Python с нуля

class ArpackSpectralClustering:
    def __init__(self, n_clusters=8, gamma=1.0, random_state=None):
        self.n_clusters = n_clusters
        self.gamma = gamma
        self.random_state = random_state

    @staticmethod
    def _deterministic_vector_sign_flip(u):
        # Flip the sign of the vectors to make them deterministic
        max_abs_rows = np.argmax(np.abs(u), axis=1)
        signs = np.sign(u[range(u.shape[0]), max_abs_rows])

        return u * signs[:, np.newaxis]

    def _spectral_embedding(self, affinity):
        laplacian, diag_vertex_degrees = csgraph_laplacian(affinity, normed=True, return_diag=True)
        laplacian *= -1

        arpack_v0 = np.random.RandomState(self.random_state).uniform(-1, 1, laplacian.shape[0])
        _, evecs = eigsh(laplacian, k=self.n_clusters, sigma=1.0, which="LM", tol=0, v0=arpack_v0)
        norm_evecs = evecs.T[self.n_clusters::-1] / diag_vertex_degrees
        embedding = self._deterministic_vector_sign_flip(norm_evecs)

        return embedding[:self.n_clusters].T

    def fit_predict(self, X):
        affinity_matrix = rbf_kernel(X, gamma=self.gamma)
        embedding = self._spectral_embedding(affinity_matrix)
        kmeans = KMeans(n_clusters=self.n_clusters, n_init='auto', random_state=self.random_state)
        labels = kmeans.fit_predict(embedding)

        return labels

Загрузка датасета

X3, y3 = make_moons(n_samples=200, noise=0.05, random_state=0)
X3 = StandardScaler().fit_transform(X3)
print(y3)


[0 1 1 0 1 1 0 1 0 1 0 1 1 1 0 0 0 1 0 0 1 1 0 1 0 1 1 1 1 0 0 0 1 1 0 1 1
 0 0 1 1 0 0 1 1 0 0 0 1 1 0 1 1 0 1 0 0 1 0 0 1 0 1 0 1 0 0 1 0 0 1 0 1 1
 1 0 1 0 0 1 1 0 1 1 1 0 0 0 1 1 0 0 1 0 1 1 1 1 0 1 1 1 0 0 0 1 0 0 1 0 0
 0 0 0 0 1 0 1 1 0 0 0 1 0 1 0 0 1 1 1 0 0 0 1 1 1 1 0 1 0 1 1 0 0 0 0 1 1
 0 1 1 1 0 0 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 1 1 1 0 0 0 1 0 1 1 1
 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1]

Обучение моделей и оценка полученных результатов

Поскольку спектральное преобразование матрицы сходства графа позволяет выявлять скрытую геометрическую структуру данных, алгоритм спектральной кластеризации может применяться к нелинейно разделимым данным и показывать довольно хорошие результаты кластеризации сложных форм, что видно из результатов ниже.

SpectralClustering

sc = ArpackSpectralClustering(n_clusters=2, gamma=10, random_state=0)
sc_pred_res = sc.fit_predict(X3)
sc_ari = adjusted_rand_score(y3, sc_pred_res)
print(f'Adjusted Rand Score for SpectralClustering: {sc_ari}', '', sep='\n')
print('prediction', sc_pred_res, sep='\n')


Adjusted Rand Score for SpectralClustering: 1.0

prediction
[0 1 1 0 1 1 0 1 0 1 0 1 1 1 0 0 0 1 0 0 1 1 0 1 0 1 1 1 1 0 0 0 1 1 0 1 1
 0 0 1 1 0 0 1 1 0 0 0 1 1 0 1 1 0 1 0 0 1 0 0 1 0 1 0 1 0 0 1 0 0 1 0 1 1
 1 0 1 0 0 1 1 0 1 1 1 0 0 0 1 1 0 0 1 0 1 1 1 1 0 1 1 1 0 0 0 1 0 0 1 0 0
 0 0 0 0 1 0 1 1 0 0 0 1 0 1 0 0 1 1 1 0 0 0 1 1 1 1 0 1 0 1 1 0 0 0 0 1 1
 0 1 1 1 0 0 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 1 1 1 0 0 0 1 0 1 1 1
 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1]

SpectralClustering (scikit-learn)

sk_sc = SpectralClustering(n_clusters=2, gamma=10, random_state=0)
sk_sc_pred_res = sk_sc.fit_predict(X3)
sk_sc_ari = adjusted_rand_score(y3, sk_sc_pred_res)
print(f'Adjusted Rand Score for sk SpectralClustering: {sk_sc_ari}', '', sep='\n')
print('prediction', sk_sc_pred_res, sep='\n')


Adjusted Rand Score for sk SpectralClustering: 1.0

prediction
[0 1 1 0 1 1 0 1 0 1 0 1 1 1 0 0 0 1 0 0 1 1 0 1 0 1 1 1 1 0 0 0 1 1 0 1 1
 0 0 1 1 0 0 1 1 0 0 0 1 1 0 1 1 0 1 0 0 1 0 0 1 0 1 0 1 0 0 1 0 0 1 0 1 1
 1 0 1 0 0 1 1 0 1 1 1 0 0 0 1 1 0 0 1 0 1 1 1 1 0 1 1 1 0 0 0 1 0 0 1 0 0
 0 0 0 0 1 0 1 1 0 0 0 1 0 1 0 0 1 1 1 0 0 0 1 1 1 1 0 1 0 1 1 0 0 0 0 1 1
 0 1 1 1 0 0 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 1 1 1 0 0 0 1 0 1 1 1
 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1]

Визуализация прогнозов

plt.figure(figsize=(12, 5))

plt.subplot(121)
plt.scatter(X3[:, 0], X3[:, 1], c=sc_pred_res, cmap='Spectral')
plt.title('SpectralClustering')
plt.xlabel("Feature 1")
plt.ylabel("Feature 2")

plt.subplot(122)
plt.scatter(X3[:, 0], X3[:, 1], c=sk_sc_pred_res, cmap='Spectral')
plt.title('SpectralClustering (scikit-learn)')
plt.xlabel("Feature 1")

plt.show()

Ручная реализация vs scikit-learn

Преимущества и недостатки спектральной кластеризации

Преимущества:

работа с кластерами сложных форм;
возможность обработки многомерных данных из-за понижения размерности перед их кластеризацией;
устойчивость к выбросам и шуму в данных из-за учёта их глобальной структуры, а не только локальной.

Недостатки:

сложность конфигурации из-за большого количества гиперпараметров;
высокая вычислительная сложность и потребление памяти при работе с большими объемами данных, что может быть частично решено с помощью безматричных методов или случайных проекций.

Дополнительные источники

Статья «On Spectral Clustering: Analysis and an algorithm», Andrew Y. Ng, Michael I. Jordan, Yair Weiss.

Документация: описание SpectralClustering, SpectralClustering (алгоритм).

Видео: один, два, три.

DBSCAN

Более интересным алгоритмом кластеризации является DBSCAN (Density-Based Spatial Clustering of Applications with Noise), который основан на плотности точек в пространстве. Он группирует вместе точки, которые находятся близко друг к другу и отмечает как выбросы точки, которые лежат в областях с низкой плотностью. Помимо того что DBSCAN может обнаруживать кластеры произвольной формы и выбросы в данных, его главная особенность заключается в самостоятельном определении необходимого количества кластеров, что избавляет от необходимости в их подборе.

Для вычисления попарных расстояний и ближайших соседей точек в DBSCAN используется модифицированная реализация k-ближайших соседей, которая является алгоритмом обучения без учителя и представлена в scikit-learn в виде класса NearestNeighbors.

Схема образования кластера в DBSCAN

Принцип работы DBSCAN

Наиболее важными параметрами, влияющими на результат кластеризации, являются eps (максимально допустимое расстояние между точками, чтобы считаться соседями) и min_samples (минимальное количество точек в окрестности другой точки, чтобы считаться базовой точкой), а сами же точки в данных подразделяются на 3 вида:

Core points (базовые точки) — точки в кластере, имеющие min_samples соседей в своём окружении eps или более. Это означает, что точки лежат в области высокой плотности данных.
Border points (пограничные точки) — точки в кластере, которые имеют меньше, чем min_samples соседей в своём окружении eps, но лежат в окружении eps других базовых точек. Это означает, что точки лежат на границе кластеров.
Noise points (шумовые точки) — это выбросы, которые не принадлежат ни к одному кластеру, то есть точки расположены в области низкой плотности данных.

Алгоритм строится следующим образом:

1) изначально все метки кластеров помечаются как шумовые;
2) после для каждой точки в своём окружении находятся соседи и на их основе отбираются базовые точки;
3) на основе базовых точек и соседей в своём окружении, с помощью метода _dbscan_inner обновляются метки кластеров, которые и будут конечным прогнозом.

_dbscan_inner строится следующим образом:

1) непомеченным базовым точкам присваиваются текущие метки и они добавляются в очередь для дальнейшей обработки;
2) из данной очереди для каждой базовой точки находятся соседи, где каждому непомеченному соседу присваивается текущая метка и он добавляется в очередь из шага 1;
3) далее текущая метка увеличивается на 1 и шаг 2 повторяется пока очередь не станет пустой.

В результате данного процесса каждой точке присваивается метка соответствующего кластера, к которому она принадлежит. Точки, которые не принадлежат ни к одному кластеру, остаются шумовыми с меткой -1.

Импорт необходимых библиотек

import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
from sklearn.neighbors import NearestNeighbors
from sklearn.datasets import make_circles
from sklearn.metrics import adjusted_rand_score
from sklearn.preprocessing import StandardScaler

Реализация на Python с нуля

class DBSCANClustering:
    def __init__(self, eps=0.5, min_samples=5, metric='euclidean', algorithm='auto', leaf_size=30):
        self.eps = eps
        self.min_samples = min_samples
        self.metric = metric
        self.algorithm = algorithm
        self.leaf_size = leaf_size

    @staticmethod
    def _dbscan_inner(core_points, neighborhoods, labels):
        label, queue = 0, []

        for point in range(len(core_points)):
            # if the point is already assigned a label or not a core point, skip it
            if not core_points[point] or labels[point] != -1:
                continue

            labels[point] = label
            queue.append(point)

            while queue:
                current_point = queue.pop(0)
                # if the point is a core point, get it's neighbors
                if core_points[current_point]:
                    current_neighbors = neighborhoods[current_point]

                    for neighbor in current_neighbors:
                        if labels[neighbor] == -1:
                            labels[neighbor] = label
                            queue.append(neighbor)

            label += 1

    def fit_predict(self, X):
        nn = NearestNeighbors(n_neighbors=self.min_samples, radius=self.eps, metric=self.metric,
                              algorithm=self.algorithm, leaf_size=self.leaf_size)

        # find the neighbors for each point within the given radius
        neighborhoods = nn.fit(X).radius_neighbors(X, return_distance=False)
        labels = np.full(len(X), -1, dtype=np.intp)
        core_points = np.asarray([len(n) >= self.min_samples for n in neighborhoods])

        self._dbscan_inner(core_points, neighborhoods, labels)
        self.labels_ = labels

        return self.labels_

Загрузка датасета

X4, y4 = make_circles(n_samples=250, noise=0.05, factor=0.5, random_state=0)
X4 = StandardScaler().fit_transform(X4)
print(y4)


[1 0 0 1 1 1 1 0 0 1 1 1 0 1 0 0 1 1 1 0 1 0 1 0 1 0 0 0 1 0 1 0 0 1 1 1 1
 0 0 1 0 0 0 1 0 0 1 0 0 1 0 1 1 0 0 0 1 0 1 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0
 1 0 1 0 1 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 1 1 0 1 1 0 1 0 0 0 1 0 1 0 0
 1 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 1 0 1 1 1 0 1 0 1 0 1 1 0 0 0 0 0
 0 0 0 1 1 0 1 1 0 0 1 1 1 0 0 0 0 1 1 1 1 1 0 1 0 0 0 0 0 1 0 0 0 1 0 0 1
 1 0 0 1 0 1 1 1 0 0 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 0 1 0 0 1 1 0 1 1 0 1 1
 0 0 0 1 0 1 1 1 0 1 1 0 1 0 1 0 0 0 0 1 0 0 1 0 1 0 0 1]

Обучение моделей и оценка полученных результатов

Как можно заметить, DBSCAN также отлично справился с кластеризацией данных сложной формы, однако выбор оптимальных eps и min_samples на практике может оказаться довольно трудной задачей, поскольку данные параметры существенно влияют на результаты кластеризации.

Частично данную проблему можно решить с использованием HDBSCAN — модификации DBSCAN, которая автоматически находит подходящее значение eps для каждого кластера, используя иерархический подход, что позволяет определять кластеры разной плотности и повысить устойчивость к выбросам.

Ещё одной интересной модификацией, похожей на HDBSCAN, является OPTICS (Ordering Points To Identify the Clustering Structure), где используется граф достижимости, который определяет достижимое расстояние для каждой точки, которая в дальнейшем будет относиться к ближайшему кластеру. Такой подход позволяет ещё лучше определять кластеры разной плотности, особенно если они расположены близко друг к другу, однако это увеличивает время работы алгоритма.

DBSCAN

dbscan = DBSCANClustering(eps=0.3, min_samples=3)
dbscan_pred_res = dbscan.fit_predict(X4)
dbscan_ari = adjusted_rand_score(y4, dbscan_pred_res)
print(f'Adjusted Rand Score for DBSCAN: {dbscan_ari}', '', sep='\n')
print('prediction', dbscan_pred_res, sep='\n')


Adjusted Rand Score for DBSCAN: 1.0

prediction
[0 1 1 0 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 1 0 1 0 1 0 1 1 1 0 1 0 1 1 0 0 0 0
 1 1 0 1 1 1 0 1 1 0 1 1 0 1 0 0 1 1 1 0 1 0 1 0 1 1 0 0 0 1 0 0 0 0 0 0 1
 0 1 0 1 0 1 1 1 1 1 1 0 0 1 1 1 0 1 1 0 1 1 0 0 1 0 0 1 0 1 1 1 0 1 0 1 1
 0 0 0 1 1 1 1 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 1 1 1 1 1
 1 1 1 0 0 1 0 0 1 1 0 0 0 1 1 1 1 0 0 0 0 0 1 0 1 1 1 1 1 0 1 1 1 0 1 1 0
 0 1 1 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 0 1 0 0 1 0 0
 1 1 1 0 1 0 0 0 1 0 0 1 0 1 0 1 1 1 1 0 1 1 0 1 0 1 1 0]

DBSCAN (scikit-learn)

sk_dbscan = DBSCAN(eps=0.3, min_samples=3)
sk_dbscan_pred_res = sk_dbscan.fit_predict(X4)
sk_dbscan_ari = adjusted_rand_score(y4, sk_dbscan_pred_res)
print(f'Adjusted Rand Score for sk DBSCAN: {sk_dbscan_ari}', '', sep='\n')
print('prediction', sk_dbscan_pred_res, sep='\n')


Adjusted Rand Score for sk DBSCAN: 1.0

prediction
[0 1 1 0 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 1 0 1 0 1 0 1 1 1 0 1 0 1 1 0 0 0 0
 1 1 0 1 1 1 0 1 1 0 1 1 0 1 0 0 1 1 1 0 1 0 1 0 1 1 0 0 0 1 0 0 0 0 0 0 1
 0 1 0 1 0 1 1 1 1 1 1 0 0 1 1 1 0 1 1 0 1 1 0 0 1 0 0 1 0 1 1 1 0 1 0 1 1
 0 0 0 1 1 1 1 0 1 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 1 1 1 1 1
 1 1 1 0 0 1 0 0 1 1 0 0 0 1 1 1 1 0 0 0 0 0 1 0 1 1 1 1 1 0 1 1 1 0 1 1 0
 0 1 1 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 0 1 0 0 1 0 0
 1 1 1 0 1 0 0 0 1 0 0 1 0 1 0 1 1 1 1 0 1 1 0 1 0 1 1 0]

Визуализация прогнозов

plt.figure(figsize=(12, 5))

plt.subplot(1, 2, 1)
plt.scatter(X4[:, 0], X4[:, 1], c=dbscan_pred_res, cmap='rainbow')
plt.title('DBSCAN')
plt.xlabel("Feature 1")
plt.ylabel("Feature 2")

plt.subplot(1, 2, 2)
plt.scatter(X4[:, 0], X4[:, 1], c=sk_dbscan_pred_res, cmap='rainbow')
plt.title('DBSCAN (scikit-learn)')
plt.xlabel("Feature 1")

plt.show()

Ручная реализация vs scikit-learn

Преимущества и недостатки DBSCAN

Преимущества:

устойчив к выбросам;
не требуется заранее указывать количество кластеров;
способность находить кластеры произвольной формы, а также шумные точки в данных.

Недостатки:

плохая работа с кластерами разной плотности;
требуется большой объём памяти для хранения расстояний между всеми точками;
высокая чувствительность к выбору параметров eps и min_samples, что может сильно повлиять на качество кластеризации в негативную сторону.

Дополнительные источники

Статьи:

«DBSCAN: Optimal Rates For Density-Based Cluster Estimation», Daren Wang, Xinyang Lu and Alessandro Rinaldo;
«HDBSCAN: Density based Clustering over Location Based Services», Md Farhadur Rahman, Weimo Liu Saad Bin Suhaim, Saravanan Thirumuruganathan, Nan Zhang, Gautam Das;
«OPTICS: Ordering Points To Identify the Clustering Structure», Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Jörg Sander.

Документация:

описание DBSCAN ;
описание HDBSCAN ;
описание OPTICS ;
DBSCAN (алгоритм);
HDBSCAN (алгоритм);
OPTICS (алгоритм).

Видео:

DBSCAN: один, два, три.
HDBSCAN: один, два.
OPTICS: один, два.

Affinity Propagation

Ещё более продвинутым подходом относительно предыдущего алгоритма кластеризации является метод распространения близости (affinity propagation), который основан на концепции соотношения между данными и выборе из них экземпляров — наиболее репрезентативных образцов, которые представляются центроидами кластеров и группируют возле себя все остальные данные.

Соотношения между данными описываются с помощью матриц сходства S (similarity matrix), доступности A (availability matrix) и ответственности R (responsibility matrix), а наиболее важными параметрами при настройке алгоритма являются damping (фактор затухания, который не дает алгоритму слишком быстро менять своё мнение о том, какие точки данных лучше всего подходят друг другу) и preference (мера предпочтения точки быть экземпляром для себя или для других точек: чем больше это значение, тем больше вероятность быть экземпляром).

Принцип работы Affinity Propagation

Рассмотрим следующий пример для лучшего понимания сути данного алгоритма на интуитивном уровне. Представьте, что в школе есть много учеников, которые хотят найти своих друзей. Каждый ученик имеет свои предпочтения с кем он хочет дружить, исходя из общих интересов, характера, внешности и так далее. Например, один ученик любит футбол, другой ученик любит музыку, третий ученик любит математику. Эти предпочтения можно измерить числом, которое показывает насколько сильно ученик хочет дружить с другим учеником. Это называется сходством: чем оно больше, тем больше шансов, что ученики станут друзьями.

В данном случае Affinity propagation — это алгоритм, который помогает ученикам найти своих друзей на основе их предпочтений следующим образом:

Сначала каждый ученик оценивает насколько он хочет дружить с другими учениками. Например, ученик A может сказать, что он хочет дружить с учеником B на 8 из 10, с учеником C на 6 из 10, с учеником D на 4 из 10 и так далее. Эти оценки можно рассчитать с помощью отрицательного квадратичного евклидова расстояния и записать в виде матрицы сходства, где каждая строка и столбец соответствует ученику, а каждая ячейка содержит сходство между двумя учениками.

Затем каждый ученик отправляет сообщения другим ученикам, в которых говорит насколько он хочет, чтобы они были его друзьями. Это называется ответственностью. Ответственность — это степень с которой ученик выбирает другого ученика в качестве своего друга. Ответственность зависит не только от сходства, но и от того насколько другие ученики хотят быть друзьями с тем же учеником. Например, если ученик A хочет дружить с учеником B, но ученик B не хочет дружить с учеником A, то ответственность ученика A к ученику B будет низкой. Ну а если ученик A хочет дружить с учеником C, и ученик C тоже хочет дружить с учеником A, то ответственность ученика A к ученику C будет высокой. Ответственность можно вычислить по формуле:

$r(i, k) = s(i, k) - \max_{k' \neq k} \{ a(i, k') + s(i, k') \}$

где r(i, k) — это ответственность ученика i к ученику k, s(i, k) — это сходство ученика i к ученику k, a(i, k') — это доступность ученика i к ученику k', которая будет объяснена далее. Ответственность можно также записать в виде матрицы, где каждая строка и столбец соответствует ученику, а каждая ячейка содержит ответственность между двумя учениками.

Далее каждый ученик получает сообщения от других учеников, в которых они говорят насколько они хотят, чтобы он был их другом. Это называется доступностью. Доступность — это степень с которой ученик подходит для роли друга для другого ученика. Доступность зависит не только от ответственности, но и от того, насколько другие ученики подходят для роли друзей для того же ученика. Например, если ученик A хочет дружить с учеником B и ученик B хочет дружить с учеником A, то доступность ученика A к ученику B будет высокой. Ну а если ученик A хочет дружить с учеником C, но ученик C не хочет дружить с учеником A, то доступность ученика A к ученику C будет низкой. Доступность можно вычислить по формуле:

$a(i, k) = \min \{ 0, r(k, k) + \sum_{i' \neq i, k} \max \{ 0, r(i', k) \} \}$

где a(i, k) — это доступность ученика i к ученику k, r(k, k) — это ответственность ученика k к себе, r(i', k) - это ответственность другого ученика i' к ученику k. Доступность можно также записать в виде матрицы, где каждая строка и столбец соответствует ученику, а каждая ячейка содержит доступность между двумя учениками.

Алгоритм повторяет эти шаги, пока не найдет оптимальное решение, в котором каждый ученик имеет своего друга. Этот друг называется экземпляром. Экземпляры — это ученики, которые лучше всего подходят для роли друзей для других учеников. Количество экземпляров зависит от того, какие предпочтения задаются для учеников. Если предпочтения не задаются, то они равны медиане сходств. Экземпляры можно определить по формуле:

$e(i) = \arg \max_k \{ r(i, k) + a(i, k) \}$

где e(i) — это экземпляр ученика i, r(i, k) — это ответственность ученика i к ученику k, a(i, k) — это доступность ученика i к ученику k. Эта формула означает, что ученик i выбирает в качестве своего друга того ученика k, для которого сумма ответственности и доступности максимальна. Если ученик i выбирает себя в качестве своего друга, то он является экземпляром. Если ученик i выбирает другого ученика k в качестве своего друга, то он принадлежит к тому же кластеру, что и ученик k. Кластер — это группа учеников, которые имеют одного и того же друга-экземпляра.

Данный алгоритм строится следующим образом:

1) на основе отрицательного квадратичного расстояния находится матрица сходства, а также нулями инициализируются матрицы доступности и ответственности;
2) из матрицы сходства удаляются вырождения, а также добавляется небольшой шум;
3) далее итеративно обновляются значения матриц доступности и ответственности на основе временной матрицы, представленной изначально как сумма матриц сходства и доступности, чтобы найти максимальное сходство между точками данных и потенциальными экземплярами;
4) из этой матрицы вычисляются максимальные значения по столбцам, а также вторые по величине значения, которые используются для вычитания из матрицы сходства, чтобы получить новую матрицу ответственности;
5) при обновлении значений матрицы доступности, временная матрица заполняется положительными значениями матрицы ответственности, чтобы посчитать сумму сообщений между точками о том, насколько сильно они хотят быть экземплярами.
6) затем из данной матрицы вычитается её сумма по столбцам, чтобы получить отрицательную матрицу доступности, а также временная матрица обрезается по нулю для получения положительной матрицы доступности;
7) также при обновлении значений матрицы доступности и ответственности к временной матрице применяется коэффициент затухания для избегания численных колебаний при обновлении значений;
8) экземпляры с положительной суммой ответственности и доступности становятся центрами кластеров;
9) после каждой итерации проверяется условие сходимости алгоритма с использованием матрицы сходимости экземпляров: если число экземпляров не меняется в течение заданного числа итераций или если число итераций достигает максимума, то алгоритм останавливается;
10) в конце уточняется итоговый набор экземпляров и меток кластеров через выбор лучших экземпляров для каждого кластера из его членов на основе максимальной суммы сходств между ними;
11) полученные метки кластеров и будут итоговым прогнозом.

Импорт необходимых библиотек

import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import make_blobs
from sklearn.cluster import AffinityPropagation
from sklearn.metrics import euclidean_distances, adjusted_rand_score

Реализация на Python с нуля

class AffinityPropagationClustering:
    def __init__(self, damping=0.5, max_iter=200, convergence_iter=15, preference=None, random_state=0):
        self.damping = damping
        self.max_iter = max_iter
        self.convergence_iter = convergence_iter
        self.preference = preference
        self.random_state = random_state

    @staticmethod
    def _affinity_propagation_inner(similarity_matrix, preference, convergence_iter, max_iter,
                                   damping, random_state):
        rng = np.random.RandomState(random_state)
        n_samples = similarity_matrix.shape[0]
        samples_indexes = np.arange(n_samples)

        # place preference on the diagonal of similarity matrix
        similarity_matrix.flat[:: (n_samples + 1)] = preference
        availability_matrix = np.zeros((n_samples, n_samples))
        responsibility_matrix = np.zeros((n_samples, n_samples))  # initialize messages
        exemplars_convergence_matrix = np.zeros((n_samples, convergence_iter))

        # remove degeneracies
        similarity_matrix += (np.finfo(similarity_matrix.dtype).eps * similarity_matrix +
                              np.finfo(similarity_matrix.dtype).tiny * 100) * \
                              rng.standard_normal(size=(n_samples, n_samples))

        for iter in range(max_iter):
            temp_matrix = availability_matrix + similarity_matrix   # compute responsibilities
            max_indexes = np.argmax(temp_matrix, axis=1)
            max_values = temp_matrix[samples_indexes, max_indexes]
            temp_matrix[samples_indexes, max_indexes] = -np.inf
            second_max_values = np.max(temp_matrix, axis=1)

            # temp_matrix = new_responsibility_matrix
            np.subtract(similarity_matrix, max_values[:, None], temp_matrix)
            max_responsibility = similarity_matrix[samples_indexes, max_indexes] - second_max_values
            temp_matrix[samples_indexes, max_indexes] = max_responsibility

            # damping
            temp_matrix *= 1 - damping
            responsibility_matrix *= damping
            responsibility_matrix += temp_matrix

            # temp_matrix = Rp; compute availabilities
            np.maximum(responsibility_matrix, 0, temp_matrix)
            temp_matrix.flat[:: n_samples + 1] = responsibility_matrix.flat[:: n_samples + 1]

            # temp_matrix = -new_availability_matrix
            temp_matrix -= np.sum(temp_matrix, axis=0)
            diag_availability_matrix = np.diag(temp_matrix).copy()
            temp_matrix.clip(0, np.inf, temp_matrix)
            temp_matrix.flat[:: n_samples + 1] = diag_availability_matrix

            # damping
            temp_matrix *= 1 - damping
            availability_matrix *= damping
            availability_matrix -= temp_matrix

            # check for convergence
            exemplar = (np.diag(availability_matrix) + np.diag(responsibility_matrix)) > 0
            exemplars_convergence_matrix[:, iter % convergence_iter] = exemplar
            n_exemplars = np.sum(exemplar, axis=0)

            if iter >= convergence_iter:
                exemplars_sum = np.sum(exemplars_convergence_matrix, axis=1)
                unconverged = np.sum((exemplars_sum == convergence_iter) +
                                     (exemplars_sum == 0)) != n_samples

                if (not unconverged and (n_exemplars > 0)) or (iter == max_iter):
                    break

        exemplar_indixes = np.flatnonzero(exemplar)
        n_exemplars = exemplar_indixes.size  # number of detected clusters

        if n_exemplars > 0:
            cluster_indices = np.argmax(similarity_matrix[:, exemplar_indixes], axis=1)
            cluster_indices[exemplar_indixes] = np.arange(n_exemplars)  # Identify clusters

            # refine the final set of exemplars and clusters and return results
            for k in range(n_exemplars):
                cluster_members = np.where(cluster_indices == k)[0]
                best_k = np.argmax(np.sum(similarity_matrix[cluster_members[:, np.newaxis],
                                                            cluster_members], axis=0))
                exemplar_indixes[k] = cluster_members[best_k]

            cluster_indices = np.argmax(similarity_matrix[:, exemplar_indixes], axis=1)
            cluster_indices[exemplar_indixes] = np.arange(n_exemplars)
            labels = exemplar_indixes[cluster_indices]

            # Reduce labels to a sorted, gapless, list
            cluster_centers_indices = np.unique(labels)
            labels = np.searchsorted(cluster_centers_indices, labels)
        else:
            cluster_centers_indices = []
            labels = np.array([-1] * n_samples)

        return cluster_centers_indices, labels

    def fit_predict(self, X):
        self.affinity_matrix_ = -euclidean_distances(X, squared=True)

        if self.preference is None:
            self.preference = np.median(self.affinity_matrix_)

        params = (self.affinity_matrix_, self.preference, self.convergence_iter, self.max_iter,
                  self.damping, self.random_state)

        self.cluster_centers_indices_, self.labels_ = self._affinity_propagation_inner(*params)
        self.cluster_centers_ = X[self.cluster_centers_indices_]

        return self.labels_

Код для отрисовки графика

def plot_connected_points(X, labels, centers, cmap):
    for i in range(len(X)):
        color = cmap(labels[i] / len(centers))
        plt.plot([X[i, 0], centers[labels[i], 0]], [X[i, 1], centers[labels[i], 1]], c=color, alpha=0.8)

Загрузка датасета

X5, y5 = make_blobs(n_samples=300, centers=9, cluster_std=0.5, random_state=0)
print(y5)


[1 1 1 6 5 7 0 3 2 5 8 4 1 2 0 1 6 2 1 6 6 0 6 2 5 5 5 8 8 4 7 3 8 8 0 7 4
 6 2 0 4 4 7 1 7 5 8 0 5 4 0 3 8 8 2 2 4 7 6 7 4 5 4 5 3 8 4 8 8 4 6 6 2 3
 7 7 4 8 4 1 4 8 7 3 7 8 6 1 3 7 5 0 8 3 5 2 4 2 2 2 7 4 6 2 2 7 5 5 7 2 7
 0 5 7 1 5 3 2 8 3 1 4 2 1 8 5 1 5 5 2 2 1 6 7 4 3 3 3 5 3 6 6 6 5 4 4 2 8
 6 5 7 0 8 8 8 1 6 1 6 6 0 7 7 6 0 8 0 3 6 4 7 3 1 6 0 0 4 1 5 6 1 2 1 0 8
 3 0 7 5 4 3 0 5 2 1 4 6 1 0 0 0 3 8 5 0 6 0 1 5 4 8 2 4 0 1 6 3 7 0 8 4 8
 1 8 1 5 0 0 7 5 4 4 3 0 7 3 2 4 3 5 0 7 6 1 0 7 1 3 5 1 7 3 6 7 6 2 1 3 8
 5 2 3 1 4 6 2 3 8 0 1 6 2 7 6 0 7 1 4 3 5 4 0 2 2 2 1 8 8 7 3 2 0 3 2 3 6
 5 8 2 3]

Обучение моделей и оценка полученных результатов

Affinity Propagation показал отличный результат без настройки параметров, определив верно не только количество кластеров, но и присвоив метки всем точкам данных. Данный алгоритм также способен показывать хорошие результаты для кластеров любой формы и плотности, однако может потребоваться настройка параметров, но это всё равно проще, чем в случае с DBSCAN или HDBSCAN.

AffinityPropagation

ap = AffinityPropagationClustering()
ap_pred_res = ap.fit_predict(X5)
ap_ari = adjusted_rand_score(y5, ap_pred_res)
print(f'Adjusted Rand Score for AffinityPropagation: {ap_ari}', '', sep='\n')
print('prediction', ap_pred_res, sep='\n')


Adjusted Rand Score for AffinityPropagation: 1.0

prediction
[1 1 1 7 6 0 8 5 2 6 3 4 1 2 8 1 7 2 1 7 7 8 7 2 6 6 6 3 3 4 0 5 3 3 8 0 4
 7 2 8 4 4 0 1 0 6 3 8 6 4 8 5 3 3 2 2 4 0 7 0 4 6 4 6 5 3 4 3 3 4 7 7 2 5
 0 0 4 3 4 1 4 3 0 5 0 3 7 1 5 0 6 8 3 5 6 2 4 2 2 2 0 4 7 2 2 0 6 6 0 2 0
 8 6 0 1 6 5 2 3 5 1 4 2 1 3 6 1 6 6 2 2 1 7 0 4 5 5 5 6 5 7 7 7 6 4 4 2 3
 7 6 0 8 3 3 3 1 7 1 7 7 8 0 0 7 8 3 8 5 7 4 0 5 1 7 8 8 4 1 6 7 1 2 1 8 3
 5 8 0 6 4 5 8 6 2 1 4 7 1 8 8 8 5 3 6 8 7 8 1 6 4 3 2 4 8 1 7 5 0 8 3 4 3
 1 3 1 6 8 8 0 6 4 4 5 8 0 5 2 4 5 6 8 0 7 1 8 0 1 5 6 1 0 5 7 0 7 2 1 5 3
 6 2 5 1 4 7 2 5 3 8 1 7 2 0 7 8 0 1 4 5 6 4 8 2 2 2 1 3 3 0 5 2 8 5 2 5 7
 6 3 2 5]

AffinityPropagation (scikit-learn)

sk_ap = AffinityPropagation()
sk_ap_pred_res = sk_ap.fit_predict(X5)
sk_ap_ari = adjusted_rand_score(y5, sk_ap_pred_res)
print(f'Adjusted Rand Score for sk AffinityPropagation: {sk_ap_ari}', '', sep='\n')
print('prediction', sk_ap_pred_res, sep='\n')


Adjusted Rand Score for sk AffinityPropagation: 1.0

prediction
[1 1 1 7 6 0 8 5 2 6 3 4 1 2 8 1 7 2 1 7 7 8 7 2 6 6 6 3 3 4 0 5 3 3 8 0 4
 7 2 8 4 4 0 1 0 6 3 8 6 4 8 5 3 3 2 2 4 0 7 0 4 6 4 6 5 3 4 3 3 4 7 7 2 5
 0 0 4 3 4 1 4 3 0 5 0 3 7 1 5 0 6 8 3 5 6 2 4 2 2 2 0 4 7 2 2 0 6 6 0 2 0
 8 6 0 1 6 5 2 3 5 1 4 2 1 3 6 1 6 6 2 2 1 7 0 4 5 5 5 6 5 7 7 7 6 4 4 2 3
 7 6 0 8 3 3 3 1 7 1 7 7 8 0 0 7 8 3 8 5 7 4 0 5 1 7 8 8 4 1 6 7 1 2 1 8 3
 5 8 0 6 4 5 8 6 2 1 4 7 1 8 8 8 5 3 6 8 7 8 1 6 4 3 2 4 8 1 7 5 0 8 3 4 3
 1 3 1 6 8 8 0 6 4 4 5 8 0 5 2 4 5 6 8 0 7 1 8 0 1 5 6 1 0 5 7 0 7 2 1 5 3
 6 2 5 1 4 7 2 5 3 8 1 7 2 0 7 8 0 1 4 5 6 4 8 2 2 2 1 3 3 0 5 2 8 5 2 5 7
 6 3 2 5]

Визуализация прогнозов

plt.figure(figsize=(12, 5))

plt.subplot(121)
plt.scatter(X5[:, 0], X5[:, 1], c=ap_pred_res, cmap='rainbow', s=10)
plt.scatter(ap.cluster_centers_[:, 0], ap.cluster_centers_[:, 1], c='black', s=50)
plt.title('AffinityPropagation')
plt.xlabel("Feature 1")
plt.ylabel("Feature 2")
plot_connected_points(X5, ap_pred_res, ap.cluster_centers_, plt.cm.rainbow)

plt.subplot(122)
plt.scatter(X5[:, 0], X5[:, 1], c=sk_ap_pred_res, cmap='rainbow', s=10)
plt.scatter(sk_ap.cluster_centers_[:, 0], sk_ap.cluster_centers_[:, 1], c='black', s=50)
plt.title('AffinityPropagation (scikit-learn)')
plt.xlabel("Feature 1")
plot_connected_points(X5, sk_ap_pred_res, sk_ap.cluster_centers_, plt.cm.rainbow)

plt.show()

Ручная реализация vs scikit-learn

Преимущества и недостатки Affinity Propagation

Преимущества:

высокая точность;
автоматическое определение количества кластеров;
не чувствителен к выбору начальных значений;
небольшое количество гиперпараметров для настройки.

Недостатки:

возможна чувствительность к выбросам и шуму в данных;
высокая сложность по времени выполнения и использованию памяти, что делает затруднительным его применение к данным большого размера.

Не смотря на то, что Affinity Propagation является далеко не самым быстрым алгоритмом, на данный момент существует несколько модификаций, способных значительно повысить его скорость. Среди наиболее интересных модификаций можно выделить следующие:

Hierarchical Affinity Propagation (HAP) — алгоритм кластеризации с использованием Affinity Propagation несколько раз на разных уровнях данных. Сначала находятся экземпляры на небольшом подмножестве данных, которые после применяются ко всему набору данных. Такой подход позволяет сократить время выполнения и уменьшить количество сообщений, передаваемых между точками, однако это может повлиять на качество кластеризации.
Fast Affinity Propagation — модификация на основе обрезаний сообщений, которая базируется на двух основных идеях. Во-первых, сокращается размер матрицы сходства путем выбора небольшого подмножества экземпляров в качестве кандидатов в прототипы, а также вычисления сходства только между ними и всеми остальными экземплярами. Во-вторых, используется многомерный поиск для определения параметра предпочтения путем разбиения интервала возможных значений предпочтения на несколько подынтервалов и запуска алгоритма на каждом из них параллельно. Затем выбирается тот подынтервал, который дает наилучшее качество кластеризации по некоторому установленному критерию.
Affinity Propagation на основе пиков плотности — двухэтапный алгоритм кластеризации (DDAP), который сначала определяет пики плотности в данных с помощью алгоритма DDC (Density peaks and Distance-based Clustering), а затем использует стандартный Affinity Propagation для поиска экземпляров, которые близки к этим пикам. Такой подход позволяет значительно уменьшить количество вычислений при сопоставимом качестве кластеризации.

Дополнительные источники

Статьи:

«Extended Affinity Propagation: Global Discovery and Local Insights», Rayyan Ahmad Khan, Rana Ali Amjad, Martin Kleinsteuber;
«Hierarchical Affinity Propagation», Inmar E. Givoni, Clement Chung, Brendan J. Frey;
«Fast Affinity Propagation Clustering based on Machine Learning», Shailendra Kumar Shrivastava, Dr. J.L. Rana and Dr. R.C. Jain;
«Fast Clustering by Affinity Propagation Based on Density Peaks», Yang Li, Chonghui Guo, Leilei Sun.

Документация:

описание Affinity Propagation, Affinity Propagation (алгоритм).

Видео: один, два.

The end

Вот и подошёл к концу обзор данной темы. Очень надеюсь, что вам понравилось, поскольку в дальнейшем я планирую опубликовать в подобном формате статьи по всем популярным алгоритмам машинного обучения с их реализацией с нуля на Python.

Всем успехов!

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8 мар. 2024 г.

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My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1
05.06.26 18:26 edengarcia

When most people hear the words crypto recovery service, their guard immediately goes up—and for good reason. In today’s online environment, finding a legitimate service feels like finding a needle in a haystack. Ask about trusted crypto recovery on any major forum, and you’ll be met with hostility. It’s become a cultural bias that victims often prefer filing police reports rather than seeking private help, fearing that speaking openly will only attract more scammers. But silence doesn’t bring your funds back. Website https://techyforcecyberretrieval.com Whatsapp +15617263697 The reality is harsh: Less than 10% of “recovery agencies” online are genuine. Fraudsters have mastered the art of mimicking trust. So, how do you separate the wolves from the professionals? The Golden Rule: No Upfront Fees If there is one sign that separates a scam from a legitimate operation, it is the payment model. Legitimate recovery companies never ask for upfront fees. Predatory scams will demand "processing fees," "software licenses," or "tax payments" before they lift a finger. A genuine agency knows its value lies in results, not promises. They operate on a success-based fee —typically around 10% of the recovered amount. Simply put: No recovery, no payment. Enter TechY Force Cyber Retrieval At TechY Force Cyber Retrieval, we understand why you’re skeptical. We built our model to eliminate that risk. We specialize in the fast, forensic tracking of lost crypto assets. Because we are confident in our technology and methodology, we don’t need your money to start working—we need your trust. We only get paid once you receive your crypto. How to Spot a Legitimate Partner Beyond the fee structure, keep these signs in mind: 1. Transparency: They explain how without asking for your private keys or seed phrase. 2. Realism: They don’t promise 100% success on impossible cases but offer honest assessments. 3. Speed: Time is critical in blockchain tracing. Legitimate firms act fast. Website https://techyforcecyberretrieval.com Whatsapp +15617263697 Don’t let the fear of secondary scams prevent you from seeking justice. Choose a partner who puts their money where their mouth is. TechY Force Cyber Retrieval: Fast. Secure. Success-based. Disclaimer: Always conduct your own due diligence. Legitimate firms will never ask for your wallet credentials.
07.06.26 08:58 keithwilson9899

ETHEREUM RECOVERY ASSISTANCE: CAPITAL CRYPTO RECOVER HELPED ME RECOVER $98,000 WORTH OF LOST ETH In cases of cryptocurrency scams, having accurate information and trusted support is essential. I would like to recommend Capital Crypto Recover Service, a professional team that specializes in assisting individuals with the recovery of lost or stolen Bitcoin and Ethereum (ETH). Their experienced experts are dedicated to helping victims of digital asset fraud by carefully analyzing each case, developing strategic recovery plans, Capital Crypto Recover Service knowledgeable team's primary goals are to satisfy clients and offer significant support and working diligently toward fund retrieval. The team is committed to providing reliable assistance and maintaining a high level of client satisfaction. Based on my assessment, their reputation professionalism and a strong commitment to their clients. If you have experienced a cryptocurrency loss, you can contacting them for further assistance Phone (Call/Text): +1 (336) 390-6684 Email: [email protected] Alternate Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
07.06.26 08:58 keithwilson9899

ETHEREUM RECOVERY ASSISTANCE: CAPITAL CRYPTO RECOVER HELPED ME RECOVER $98,000 WORTH OF LOST ETH In cases of cryptocurrency scams, having accurate information and trusted support is essential. I would like to recommend Capital Crypto Recover Service, a professional team that specializes in assisting individuals with the recovery of lost or stolen Bitcoin and Ethereum (ETH). Their experienced experts are dedicated to helping victims of digital asset fraud by carefully analyzing each case, developing strategic recovery plans, Capital Crypto Recover Service knowledgeable team's primary goals are to satisfy clients and offer significant support and working diligently toward fund retrieval. The team is committed to providing reliable assistance and maintaining a high level of client satisfaction. Based on my assessment, their reputation professionalism and a strong commitment to their clients. If you have experienced a cryptocurrency loss, you can contacting them for further assistance Phone (Call/Text): +1 (336) 390-6684 Email: [email protected] Alternate Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
07.06.26 21:00 gordondowney9

Email: [email protected] Telegram —digitallightsolution, https://t.me/digitallightsolution Losing my USDT to a fraudulent cryptocurrency platform was one of the most painful and overwhelming experiences I have ever faced. I felt devastated, confused, and ashamed that something I had placed my trust in had turned out to be a scam. For a while, I did not know where to turn or whether there was any real hope of recovering what I had lost. During that very difficult time, a trusted pastor recommended Digital-Light-Solution, and although I was hesitant at first, I decided to visit their website https://digitallightsolution.com/. From my first interaction with them, I felt a sense of relief. They listened to my situation with patience and understanding, and they treated me with kindness at a time when I felt completely broken. Their team explained the process clearly, answered my questions, and kept me informed throughout. What meant the most to me was not just their professionalism, but the way they made me feel supported when I was struggling emotionally. As the process continued, I began to regain a sense of hope. They remained consistent, responsive, and committed to my case, which gave me comfort during an incredibly stressful period. In the end, Digital-Light-Solutions was able to assist with tracing my lost USDT and supporting the recovery process. The relief my family and I felt is difficult to put into words. I will always be grateful for the support, compassion, and professionalism they showed me during one of the hardest moments of my life, I highly recommend their services to anyone in need. Contact them today for assistance
07.06.26 21:00 gordondowney9

Email: [email protected] Telegram —digitallightsolution, https://t.me/digitallightsolution Losing my USDT to a fraudulent cryptocurrency platform was one of the most painful and overwhelming experiences I have ever faced. I felt devastated, confused, and ashamed that something I had placed my trust in had turned out to be a scam. For a while, I did not know where to turn or whether there was any real hope of recovering what I had lost. During that very difficult time, a trusted pastor recommended Digital-Light-Solution, and although I was hesitant at first, I decided to visit their website https://digitallightsolution.com/. From my first interaction with them, I felt a sense of relief. They listened to my situation with patience and understanding, and they treated me with kindness at a time when I felt completely broken. Their team explained the process clearly, answered my questions, and kept me informed throughout. What meant the most to me was not just their professionalism, but the way they made me feel supported when I was struggling emotionally. As the process continued, I began to regain a sense of hope. They remained consistent, responsive, and committed to my case, which gave me comfort during an incredibly stressful period. In the end, Digital-Light-Solutions was able to assist with tracing my lost USDT and supporting the recovery process. The relief my family and I felt is difficult to put into words. I will always be grateful for the support, compassion, and professionalism they showed me during one of the hardest moments of my life, I highly recommend their services to anyone in need. Contact them today for assistance
07.06.26 21:02 gordondowney9

Email: [email protected] Telegram —digitallightsolution, https://t.me/digitallightsolution Losing my USDT to a fraudulent cryptocurrency platform was one of the most painful and overwhelming experiences I have ever faced. I felt devastated, confused, and ashamed that something I had placed my trust in had turned out to be a scam. For a while, I did not know where to turn or whether there was any real hope of recovering what I had lost. During that very difficult time, a trusted pastor recommended Digital-Light-Solution, and although I was hesitant at first, I decided to visit their website https://digitallightsolution.com/. From my first interaction with them, I felt a sense of relief. They listened to my situation with patience and understanding, and they treated me with kindness at a time when I felt completely broken. Their team explained the process clearly, answered my questions, and kept me informed throughout. What meant the most to me was not just their professionalism, but the way they made me feel supported when I was struggling emotionally. As the process continued, I began to regain a sense of hope. They remained consistent, responsive, and committed to my case, which gave me comfort during an incredibly stressful period. In the end, Digital-Light-Solutions was able to assist with tracing my lost USDT and supporting the recovery process. The relief my family and I felt is difficult to put into words. I will always be grateful for the support, compassion, and professionalism they showed me during one of the hardest moments of my life, I highly recommend their services to anyone in need. Contact them today for assistance
07.06.26 21:02 gordondowney9

Email: [email protected] Telegram —digitallightsolution, https://t.me/digitallightsolution Losing my USDT to a fraudulent cryptocurrency platform was one of the most painful and overwhelming experiences I have ever faced. I felt devastated, confused, and ashamed that something I had placed my trust in had turned out to be a scam. For a while, I did not know where to turn or whether there was any real hope of recovering what I had lost. During that very difficult time, a trusted pastor recommended Digital-Light-Solution, and although I was hesitant at first, I decided to visit their website https://digitallightsolution.com/. From my first interaction with them, I felt a sense of relief. They listened to my situation with patience and understanding, and they treated me with kindness at a time when I felt completely broken. Their team explained the process clearly, answered my questions, and kept me informed throughout. What meant the most to me was not just their professionalism, but the way they made me feel supported when I was struggling emotionally. As the process continued, I began to regain a sense of hope. They remained consistent, responsive, and committed to my case, which gave me comfort during an incredibly stressful period. In the end, Digital-Light-Solutions was able to assist with tracing my lost USDT and supporting the recovery process. The relief my family and I felt is difficult to put into words. I will always be grateful for the support, compassion, and professionalism they showed me during one of the hardest moments of my life, I highly recommend their services to anyone in need. Contact them today for assistance
07.06.26 21:03 gordondowney9

Email: [email protected] Telegram —digitallightsolution, https://t.me/digitallightsolution Losing my USDT to a fraudulent cryptocurrency platform was one of the most painful and overwhelming experiences I have ever faced. I felt devastated, confused, and ashamed that something I had placed my trust in had turned out to be a scam. For a while, I did not know where to turn or whether there was any real hope of recovering what I had lost. During that very difficult time, a trusted pastor recommended Digital-Light-Solution, and although I was hesitant at first, I decided to visit their website https://digitallightsolution.com/. From my first interaction with them, I felt a sense of relief. They listened to my situation with patience and understanding, and they treated me with kindness at a time when I felt completely broken. Their team explained the process clearly, answered my questions, and kept me informed throughout. What meant the most to me was not just their professionalism, but the way they made me feel supported when I was struggling emotionally. As the process continued, I began to regain a sense of hope. They remained consistent, responsive, and committed to my case, which gave me comfort during an incredibly stressful period. In the end, Digital-Light-Solutions was able to assist with tracing my lost USDT and supporting the recovery process. The relief my family and I felt is difficult to put into words. I will always be grateful for the support, compassion, and professionalism they showed me during one of the hardest moments of my life, I highly recommend their services to anyone in need. Contact them today for assistance
07.06.26 21:04 gordondowney9

Email: [email protected] Telegram —digitallightsolution, https://t.me/digitallightsolution Losing my USDT to a fraudulent cryptocurrency platform was one of the most painful and overwhelming experiences I have ever faced. I felt devastated, confused, and ashamed that something I had placed my trust in had turned out to be a scam. For a while, I did not know where to turn or whether there was any real hope of recovering what I had lost. During that very difficult time, a trusted pastor recommended Digital-Light-Solution, and although I was hesitant at first, I decided to visit their website https://digitallightsolution.com/. From my first interaction with them, I felt a sense of relief. They listened to my situation with patience and understanding, and they treated me with kindness at a time when I felt completely broken. Their team explained the process clearly, answered my questions, and kept me informed throughout. What meant the most to me was not just their professionalism, but the way they made me feel supported when I was struggling emotionally. As the process continued, I began to regain a sense of hope. They remained consistent, responsive, and committed to my case, which gave me comfort during an incredibly stressful period. In the end, Digital-Light-Solutions was able to assist with tracing my lost USDT and supporting the recovery process. The relief my family and I felt is difficult to put into words. I will always be grateful for the support, compassion, and professionalism they showed me during one of the hardest moments of my life, I highly recommend their services to anyone in need. Contact them today for assistance
10.06.26 06:21 wendytaylor015

My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1
10.06.26 06:21 wendytaylor015

My name is Wendy Taylor, I'm from Los Angeles, i want to announce to you Viewer how Capital Crypto Recover help me to restore my Lost Bitcoin, I invested with a Crypto broker without proper research to know what I was hoarding my hard-earned money into scammers, i lost access to my crypto wallet or had your funds stolen? Don’t worry Capital Crypto Recover is here to help you recover your cryptocurrency with cutting-edge technical expertise, With years of experience in the crypto world, Capital Crypto Recover employs the best latest tools and ethical hacking techniques to help you recover lost assets, unlock hacked accounts, Whether it’s a forgotten password, Capital Crypto Recover has the expertise to help you get your crypto back. a security company service that has a 100% success rate in the recovery of crypto assets, i lost wallet and hacked accounts. I provided them the information they requested and they began their investigation. To my surprise, Capital Crypto Recover was able to trace and recover my crypto assets successfully within 24hours. Thank you for your service in helping me recover my $647,734 worth of crypto funds and I highly recommend their recovery services, they are reliable and a trusted company to any individuals looking to recover lost money. Contact email [email protected] OR Telegram @Capitalcryptorecover Call/Text Number +1 (336)390-6684 his contact: [email protected] His website: https://recovercapital.wixsite.com/capital-crypto-rec-1
10.06.26 18:09 david

Look, engaging with the authorities is a marathon, not a sprint. By methodically filing these reports, you’re not just fighting for your own funds—you’re contributing to the broader battle against crypto crime. For a deeper dive into what to do after a theft, check out [email protected] for complete guide on how to recover stolen crypto
12.06.26 17:13 keithwilson9899

ETHEREUM RECOVERY ASSISTANCE: CAPITAL CRYPTO RECOVER HELPED ME RECOVER $98,000 WORTH OF LOST ETH In cases of cryptocurrency scams, having accurate information and trusted support is essential. I would like to recommend Capital Crypto Recover Service, a professional team that specializes in assisting individuals with the recovery of lost or stolen Bitcoin and Ethereum (ETH). Their experienced experts are dedicated to helping victims of digital asset fraud by carefully analyzing each case, developing strategic recovery plans, Capital Crypto Recover Service knowledgeable team's primary goals are to satisfy clients and offer significant support and working diligently toward fund retrieval. The team is committed to providing reliable assistance and maintaining a high level of client satisfaction. Based on my assessment, their reputation professionalism and a strong commitment to their clients. If you have experienced a cryptocurrency loss, you can contacting them for further assistance Phone (Call/Text): +1 (336) 390-6684 Email: [email protected] Alternate Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
12.06.26 17:13 keithwilson9899

ETHEREUM RECOVERY ASSISTANCE: CAPITAL CRYPTO RECOVER HELPED ME RECOVER $98,000 WORTH OF LOST ETH In cases of cryptocurrency scams, having accurate information and trusted support is essential. I would like to recommend Capital Crypto Recover Service, a professional team that specializes in assisting individuals with the recovery of lost or stolen Bitcoin and Ethereum (ETH). Their experienced experts are dedicated to helping victims of digital asset fraud by carefully analyzing each case, developing strategic recovery plans, Capital Crypto Recover Service knowledgeable team's primary goals are to satisfy clients and offer significant support and working diligently toward fund retrieval. The team is committed to providing reliable assistance and maintaining a high level of client satisfaction. Based on my assessment, their reputation professionalism and a strong commitment to their clients. If you have experienced a cryptocurrency loss, you can contacting them for further assistance Phone (Call/Text): +1 (336) 390-6684 Email: [email protected] Alternate Email: [email protected] Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
14.06.26 14:53 Freeman James

Recently, I was scammed out of $332,000 in a fraudulent Bitcoin investment scheme. This devastating loss added significant stress to my already difficult health challenges, as I was also facing surgery expenses for cancer. Desperate to recover my funds, I spent countless hours researching and speaking with other victims. That effort led me to a Google post that revealed the excellent reputation of FundsRetriever. Only after many hours of digging and consulting others did I learn about their stellar track record. I decided to contact them because of their successful recovery history and encouraging client testimonials. I had no idea that this decision would become the turning point in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost funds. The process was complex, but FundsRetriever's commitment to using the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance, contact: 📧 [email protected] 📞 WhatsApp: +1 603 512 144 8, Telegram: @FundsRetriever
14.06.26 15:37 kimberlyhebert786

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
14.06.26 15:37 kimberlyhebert786

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
14.06.26 16:34 Emmi Hakola

I’m open about my experience with Bitcoin investment and losing money to scammers. That said, it is possible to recover stolen Bitcoin. I used to think recovery was impossible because that’s what I had been told. But last October, I fell for a forex scam promising extremely high returns and ended up losing nearly $87,600. After searching for help for a month, I came across a Reddit article about recovering stolen cryptocurrency. I reached out to the contact provided: [email protected] and WhatsApp +19852969146. I was scared and skeptical, having heard many bad stories, but I decided to give them a try. To my amazement, I got all my stolen Bitcoin back within a very short time. I’m not sure if I’m allowed to post links here, but you can reach out to them if you also need help.
14.06.26 16:53 James willson

I lost $328,650 to a fraudulent website that claimed to be a legitimate investment platform offering high returns. I was drawn in by the desire to earn more for myself and my family. Unfortunately, by the end of 2024, I realized it was a scam when the broker stopped responding to my emails and messages. A colleague then introduced me to ResQPro Firm, and to my surprise, they were able to trace and recover my stolen funds. Contact them at: resqprofirm AT AOL dot com | WhatsApp: +1 985 296 9146 | Telegram: ResQproFirm
14.06.26 19:38 riley777

G`DAY, I lost more than 119,000 Australian dollars to a crypto scam and it took almost everything I had saved which left me feeling like I had no future. I was stuck. I did not know where to go or how to find the money again. The wallet company is no help at all and they make it so hard to see where the coins go once they leave your account so you just feel lost. I spent days looking for a way out. Then I saw a post for a person who finds stolen money. The ad said they can track any crypto that goes missing. I wanted to check if it was real. I sent an email to [email protected] +44//// 7476618364\ to see if they could help me get my funds back. They did an amazing job. My money was back in my account in less than a week after they did a fast search and return.
15.06.26 06:12 Evan Garrison

When investing in staking platforms, proceed with caution. If your funds are stolen by a fake staking pool, the experience can be very frustrating. Rather than giving in to frustration, it's important to act quickly to improve your chances of recovering your money. Unfortunately, many victims never get their money back because scammers are often in another country or using fake identities. However, in some cases, tracking the funds is easier, especially for smart contract forensics specialists. I lost €18,500 to StakeKing. FundsRetriever found a backdoor in the contract and recovered my stake. Contact [email protected], WhatsApp +1(603)5121(448), or Telegram FUNDSRETRIEVER for assistance.
15.06.26 06:25 Glenn robble

Stop putting money into platforms promising guaranteed monthly returns of 10%, 20%, or more. These are Ponzi schemes. Your "profits" are just other victims' deposits. The moment withdrawals slow down, the scam is about to collapse. If you already have money trapped, do not send more to "unlock" your funds. That is a second scam. Instead, gather all transaction hashes and wallet addresses. Bitcoin Evolution Pro took €25,000 from me. FundsRetriever traced the funds through KYC exchanges and recovered my principal. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 06:34 Sallymarch

If IQ Option or any similar platform blocks your withdrawal citing "bonus terms" or "abnormal activity," do not argue with their chat support. They are not empowered to help you. Instead, request all trade logs and bonus terms in writing. Then get FundsRetrievers forensic specialist to audit your account. IQ Option held my €9,200 for two months. FundsRetriever reviewed my case, identified regulatory violations, and secured my full payout within 72 hours. Professional pressure works. Do it immediately. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 06:38 Sallymarch

If IQ Option or any similar platform blocks your withdrawal citing "bonus terms" or "abnormal activity," do not argue with their chat support. They are not empowered to help you. Instead, request all trade logs and bonus terms in writing. Then get FundsRetrievers forensic specialist to audit your account. IQ Option held my €9,200 for two months. FundsRetriever reviewed my case, identified regulatory violations, and secured my full payout within 72 hours. Professional pressure works. Do it immediately. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 06:41 Ewaguz

Cloud mining contracts are almost always too good to be true. I learned that the hard way with MineMax. First two months, small daily payouts. Then "maintenance fees" ate everything. Then my account was frozen. Then the website disappeared. I was heartbroken. FundsRetriever traced my payments through three shell companies to a real bank account. They froze it and got my €11,000 back. Recovery is possible even from complex scams. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 12:49 Jason

Did a scammer take your money? Fake loan, crypto fraud, romance trap, phishing—they count on you feeling helpless. Prove them wrong. FundsRetriever recovers stolen digital assets fast. No upfront payment. Ever. Backed by the FBI, Interpol, and cybercrime units. Blockchain tracing, legal freezing, and full recovery—for Bitcoin, Ethereum, USDT, Ponzi schemes, you name it. Your move: get a free case review right now. Then forensics, legal action, and your funds back. ⏳ Time is everything. 📧 FUNDSRETRIEVER @ PROTON.ME 📞 +16035121448 (WhatsApp) 📱 Telegram: @FUNDSRETRIEVER
15.06.26 12:56 Hillary

As a blockchain forensic analyst, I’ve reviewed numerous recovery cases. Fundsretriever demonstrates proper on-chain tracing, evidence preservation, and legal coordination. Their methodology helped several of my clients retrieve stolen or stuck assets. Recommended for victims seeking verifiable solutions. 📧 [email protected] Telegram @FUNDSRETRIEVER WhatsApp +1 603 512 1448
15.06.26 13:03 Feliksa Stegniy

A woman added me on Facebook, and after she suggested we become friends, we started communicating. Over time, she introduced me to a crypto trading platform called btctradingfx.com. She shared a lot of information about it, along with screenshots that made the platform seem trustworthy. Convinced by her claims, I decided to give it a try. I was promised a 10% weekly return, so I made an initial investment of $500. To my surprise, I received $5,000 back. That success encouraged me to invest more, so I put in $20,000. But when I tried to withdraw my funds, I was denied access and told I needed to deposit even more money before I could make a withdrawal. In the end, I lost a total of $43,850. It was an extremely difficult and painful experience. Fortunately, I later found a professional recovery service called ResQprofirm while searching on Google. I contacted them and provided all the evidence I had. They took my case seriously and were able to track down and recover my capital from the platform, which had been inaccessible for a long time. If you find yourself in a similar situation, you might consider reaching out to them via email at [email protected] or on WhatsApp at +19852969146, Telegram @resqprofirm Thank you, ResQPro, for your support.
15.06.26 13:05 James willson

The Most Credible Crypto Recovery Service: RESQPROFIRM RESQPROFIRM is a reliable, legitimate company that helps recover lost cryptocurrency assets. After weeks of doubting whether my lost BTC could ever be restored, I realized how widespread crypto scams have become. Caution is essential when dealing with strangers online, especially about money. While recovering stolen crypto is possible, avoiding fake "recovery companies" is just as important. Real hackers work discreetly and don't advertise openly. I was scammed multiple times while desperately seeking help. Finally, a friend introduced me to RESQPROFIRM—a trustworthy, discreet team. They handle everything from website security to crypto asset recovery. With their help, I recovered $320,000 in USDT within a week. Their professionalism, discretion, and speed were outstanding. If you've been compromised, don't lose hope—but beware of fraudsters posing as saviors. RESQPROFIRM are true professionals. I'm living proof. Contact them at [email protected], WhatsApp +19852969146, or Telegram @resqprofirm.
15.06.26 13:06 Tansy

Lost $18,500 to a fake Elon Musk crypto giveaway. Sent ETH, got nothing. Recovery pages demanded more gas fees. I stopped believing. FuNds rEtRiEveR on Te.le_gram was the real one. Email: [email protected] – WhatsApp: +1 603 512 1448
15.06.26 13:08 Sarahy billy

A REAL EXPERIENCE, EVERYONE ... PLEASE BE CAREFUL ONLINE A few weeks ago, I lost around $64,000 to a fake crypto trading platform. I was drawn in by the promise of earning 15% profit daily. It was a devastating time—I struggled to pay my bills and was financially ruined. I eventually opened up to a close friend, who recommended a crypto recovery team with highly effective methods. I contacted them, and they successfully recovered all my stolen digital assets with ease. Their service was excellent, and they acted quickly—within just 5 working days, they tracked down the scammers and returned my funds. I strongly urge anyone facing investment theft or similar issues to reach out to this team for the right solution and avoid losing large sums to fraudsters... Email: Resqprofirm @aol.com WhatsApp: +19852969146, telegram @resqprofirm
15.06.26 13:12 Cole donald

"I strongly recommend RESQPRO FIRM to anyone trying to recover lost cryptocurrency assets, including Bitcoin, USDC, USDT, Ethereum, and Trump Coin. Like many others, I was shocked to learn that crypto holdings can be stolen even when private keys are carefully protected. After a sophisticated hack wiped out my entire portfolio, I felt completely helpless. Fortunately, I was referred to RESQPRO FIRM. Their team understood the complexity of my situation and successfully recovered my funds. They were responsive, communicated clearly, and followed a careful, step-by-step process—which gave me a lot of reassurance during a stressful time. If you've experienced a similar financial loss, I encourage you to reach out to them. Their professionalism and ethical hacking skills exceeded my expectations." Contact Info: · WhatsApp: +1 (985) 2969146 · Email: [email protected] · Telegram: Resqprofirm
15.06.26 13:16 Meral Yetkiner

I recently lost $38,000 to an online platform. Initially, they requested additional deposits to grant me access to my portfolio. Despite complying, my withdrawal requests were repeatedly denied, and they continued asking for more funds. Suspecting fraudulent activity, I ceased further payments and promptly reported the matter to ResQProfirm, a firm I discovered through Google. They listened to my situation, initiated communication regarding the sequence of events, and requested all relevant evidence to support their investigation. Through their dedicated efforts, they successfully traced and recovered my funds. I extend my thanks to ResQProfirm at [email protected] and via WhatsApp at +19852969146. I urge everyone to exercise caution and thoroughly research any platform before investing.
15.06.26 13:18 Silas Olsen

A fraudulent investment scheme operated by BTCMining.limited functions as a fake return scam. In this setup, scammers lure victims with false promises of high returns. Through manipulative tactics, they gain individuals' trust and convince them to invest, ultimately leading to financial loss. If you have ever faced a cyber threat or fallen victim to an online crypto scam and need to reach the authorities, I recommend contacting [email protected]. They are a legitimate team that helps victims of online crypto scams using advanced tools.
15.06.26 13:59 Ewaguz

If a binary options broker refuses your withdrawal, do not pay any "verification fees" or "tax fees." These are lies designed to extract more money. Stop communicating with their support team – they are trained to stall. Instead, immediately document every transaction, screenshot your account balance, and contact a professional recovery specialist. BinaryBook stole €14,500 from me before I learned this. FundsRetriever traced the deposits and recovered everything within two weeks. Do not wait. Do not pay more fees. Act now. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:16 Martina k.

Stop putting money into platforms promising guaranteed monthly returns of 10%, 20%, or more. These are Ponzi schemes. Your "profits" are just other victims' deposits. The moment withdrawals slow down, the scam is about to collapse. If you already have money trapped, do not send more to "unlock" your funds. That is a second scam. Instead, gather all transaction hashes and wallet addresses. Bitcoin Evolution Pro took €25,000 from me. FundsRetriever traced the funds through KYC exchanges and recovered my principal. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:18 Garrison Good

If IQ Option or any similar platform blocks your withdrawal citing "bonus terms" or "abnormal activity," do not argue with their chat support. They are not empowered to help you. Instead, request all trade logs and bonus terms in writing. Then hire a forensic specialist to audit your account. IQ Option held my €9,200 for two months. FundsRetriever reviewed my case, identified regulatory violations, and secured my full payout within 72 hours. Professional pressure works. Do it immediately. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:22 Sallymarch

Never grant API keys with withdrawal permissions to any third-party software. This is how crypto arbitrage bots steal your funds. If you have already done this, revoke all API keys immediately. Then check your exchange transaction history. CryptoArb AI drained €7,800 from my account within hours. FundsRetriever reverse-engineered the bot's code, traced the scammer's wallet, and recovered everything. Always use "read-only" API permissions only. If you made the mistake, act fast. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:23 Glennrobble

If a binary options broker closes your account and confiscates your profits, do not accept their explanation. Demand a full audit of your trade history. Most brokers cannot justify their actions when challenged by professionals. ExpertOption stole €6,200 from me claiming "abnormal activity." FundsRetriever audited my trades, proved they were legitimate, and threatened legal action. The broker paid within 10 days. Do not let them intimidate you. Get professional help. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:25 Evan Garrison

Cloud mining contracts are almost always too good to be true. I learned that the hard way with MineMax. First two months, small daily payouts. Then "maintenance fees" ate everything. Then my account was frozen. Then the website disappeared. I was heartbroken. FundsRetriever traced my payments through three shell companies to a real bank account. They froze it and got my €11,000 back. Recovery is possible even from complex scams. Contact [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 14:26 Ewaguz

That 100% deposit bonus looks tempting, doesn't it? I took it. Big mistake. When I tried to withdraw my €4,500, Olymp Trade demanded I trade 50 times the bonus amount. Impossible by design. My money was trapped. FundsRetriever reviewed the terms and found they violated consumer protection laws in my country. They negotiated directly with Olymp Trade's legal team. Within a week, my funds were released. My advice? Never accept bonuses. But if you're already trapped, call [email protected], WhatsApp +1(603)5121(448) or Telegram FUNDSRETRIEVER.
15.06.26 16:34 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
15.06.26 16:34 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
15.06.26 16:41 Louane Mercier

It is crucial to act quickly and consult a reputable, experienced recovery specialist who will support you throughout the entire recovery process. You must provide them with transaction evidence, scammer information, and any other relevant details that could aid the investigation. With this data, the experts can trace and attempt to recover your funds from the scammers' concealed accounts or wallets. R£sQprofirm company offers recovery assistance with no upfront fees. Contact them via Telegram (@ResQprofirm), WhatsApp (+19852969146), or email ([email protected]).
15.06.26 16:45 Andrés Montero

I’m open about my experience with Bitcoin investment and losing money to scammers. That said, it is possible to recover stolen Bitcoin. I used to think recovery was impossible because that’s what I had been told. But last October, I fell for a forex scam promising extremely high returns and ended up losing nearly $87,600. After searching for help for a month, I came across a Reddit article about recovering stolen cryptocurrency. I reached out to the contact provided: [email protected] and WhatsApp +19852969146. I was scared and skeptical, having heard many bad stories, but I decided to give them a try. To my amazement, I got all my stolen Bitcoin back within a very short time. I’m not sure if I’m allowed to post links here, but you can reach out to them if you also need help.
15.06.26 16:48 Olivia Sørensen

Several months ago, investing in Bitcoin proved to be one of my most lucrative endeavors. I achieved considerable profits across multiple platforms and felt a strong sense of accomplishment. Unfortunately, the situation deteriorated when I inadvertently engaged with a fraudulent Bitcoin platform. This entity swindled me out of $92,000 USD, refused to honor my withdrawal requests, and persistently demanded further deposits. Fortunately, I encountered (R£SQPRO FIRM) online. After reporting my case to them, they acted promptly and effectively recovered my lost Bitcoin. I am sincerely grateful for their professionalism and continuous assistance. Contact: ResQprofirm AT aol.com, Telegram @resqprofirm, WhatsApp +1 9 8 5 2 9 6 9 1 4 6.
15.06.26 16:51 Viljar Yohannes

I'm willing to share my experience with Bitcoin investment and losing money to scammers. But yes, recovering stolen Bitcoin is possible. I never believed in Bitcoin recovery myself, because I was told it couldn't be done. Then, last October, I fell for a forex scam that promised unrealistically high returns, and I ended up losing nearly $70,000. I searched for help for about a month until I finally found a Reddit article about recovering stolen cryptocurrency. I reached out to the contact mentioned: [RESQPROFIRM [at] AOL DOT com] and [WhatsApp +19852969146]. I was scared and skeptical because I'd heard horror stories, but I decided to give them a try. To my surprise, I got all my stolen Bitcoin back from the scammers in a very short time. I'm not sure if I'm allowed to post links here, but you can contact them if you need help too.
15.06.26 16:58 Guimar da Rosa

Withdrawal troubles shouldn’t stress you out. I faced a similar problem, and this firm stepped in and recovered my funds. Their support truly mattered. Contact them: [ResQProFirm @aol.com] telegram @resqprofirm, WhatsApp: <+198> <5296> <9146>.
15.06.26 17:03 Andrea Escalante

If withdrawals keep getting denied, stay calm. I went through the same, and this firm helped me recover everything. Their assistance was outstanding. Contact: [[email protected]], Telegram: ResQprofirm, WhatsApp: <+198> <5296> <9146>. Withdrawal troubles shouldn’t
16.06.26 11:40 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
16.06.26 11:43 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
16.06.26 13:37 Felix Steve

MY CRYPTO WAS STOLEN – HERE'S HOW I GOT IT BACK I'm Felix Steve from Canada, and I lost $115,000 USDC to a fraudulent broker who locked me out of my wallet. After sleepless nights, a friend told me about RESQPROFIRM Recovery Service. I sent them my wallet addresses, transaction history, and chat logs. Their team used blockchain tracking to trace the stolen funds, identified the scammer's wallet, and froze the assets before they could be moved. Within 24 hours, most of my crypto was recovered. I can't thank them enough. If you need help, reach out via WhatsApp: +19852969146, email: [email protected], or TG: @resqprofirm.
16.06.26 13:45 Wills ben

SUCCESSFUL CRYPTO SCAM RECOVERY – HOW I REGAINED ACCESS TO MY LOST WALLET My name is Felix Steve, and I'm from Canada. I'm sharing my story to help others who have fallen victim to crypto fraud. A few months ago, I was lured into a fake investment scheme promoted by a broker company. With Bitcoin prices climbing, I invested heavily—only to lose $115,000 USDC when the broker locked me out of my wallet and assets. It was a harrowing experience that left me sleepless and desperate. Crypto scams are on the rise, often involving bogus trading platforms, phishing, and misleading promises. In my search for help, a fellow crypto enthusiast recommended RESQPROFIRM Recovery Service, which specializes in recovering lost or stolen funds. After checking their reviews, I reached out and supplied all the evidence—wallet addresses, transaction records, and communication logs. Their team responded immediately and launched an investigation. Using advanced blockchain tracking, they traced the stolen funds, pinpointed the scammer's wallet, and worked with authorities to freeze the assets in time. Remarkably, within just 24 hours, RESQPROFIRM recovered the bulk of my stolen crypto. I was overwhelmed with relief and gratitude. Their professionalism, transparency, and steady communication made all the difference during a very dark period. If you've been scammed, I wholeheartedly recommend contacting them via WhatsApp: +19852969146, email: [email protected], or Telegram: @resqprofirm.
18.06.26 13:31 Noemi Bernard

I never expected such outstanding results. The outcome far exceeded my expectations, and I am extremely satisfied with the successful recovery of my stolen funds totaling $49,360 from my blockchain wallet. I hold this team in the highest regard. Without a doubt, they are among the most dedicated professionals in the field of fund recovery. Keep up the exceptional work! Email: [email protected] WhatsApp: +1 985 296 9146
18.06.26 13:35 Carter Morris

My experience improved significantly thanks to ResQprofirm's expert assistance and attentive customer care. Their professionalism was evident every step of the way they were able to track and recover my stolen crypto $88,360, email: [email protected], WhatsApp +19852969146.
18.06.26 13:40 Kuybida Andriyiv

I recovered my $232,000 refund through the assistance of [email protected] and WhatsApp +19852969146. Their guidance was very helpful.
20.06.26 14:57 michaeldavenport218

I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance contact [email protected] and on Telegram OR Call Number +1 (336)390-6684 via email: [email protected] you can visit his website: https://recovercapital.wixsite.com/capital-crypto-rec-1
20.06.26 14:57 michaeldavenport218

I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance contact [email protected] and on Telegram OR Call Number +1 (336)390-6684 via email: [email protected] you can visit his website: https://recovercapital.wixsite.com/capital-crypto-rec-1
21.06.26 11:09 Maurizio Rolland

I would like to express my sincere appreciation to RESQPRO FIRM for their outstanding assistance in helping victims of online fraud. Many scammers deceive investors by blocking withdrawals and continuously demanding additional deposits, making the loss of hard-earned funds a painful experience. Fortunately, RESQPRO FIRM provides support to individuals seeking to recover funds lost to fraudulent online schemes. Contact: Email: RESQPRO FIRM at Gmail Telegram: RESQPROFIRM, [email protected], WhatsApp: +1 985 296 9146
21.06.26 11:13 Buse Fahri

It is important for more people to stand together in the fight against online fraud. Those who target innocent individuals especially vulnerable people such as seniors should be held fully accountable for their actions. Every effort to raise awareness and support victims makes a meaningful difference. The team at RESQPRO FIRM is committed to helping expose fraudulent schemes and assisting those affected by online scams. Their dedication, persistence, and passion for protecting victims are truly commendable. I sincerely appreciate the hard work and commitment shown toward this mission. Together, we can continue to educate others, support victims, and work toward a safer online environment for everyone. Contact Information: Telegram: RESQPROFIRM WhatsApp: +1 985 296 9146 Email: [email protected], [email protected]
21.06.26 11:16 علیرضا گلشن

The successful recovery of my stolen funds, totaling $1,310,000, would not have been possible without your unwavering support, dedication, and tireless efforts. I am truly grateful for the opportunity to work with such a skilled and professional team. From the very beginning, I had confidence in your ability to handle this challenging situation, and you exceeded my expectations by delivering remarkable results. Your expertise, persistence, and commitment throughout the process were exceptional. I encourage you to continue maintaining the high standards of professionalism and excellence that distinguish your work. You exemplify the qualities of a trustworthy, dedicated, and hardworking professional, and your efforts deserve sincere recognition and appreciation. Contact: Email: [email protected], [email protected], Telegram: Resqprofirm WhatsApp: +1 985 296 9146
22.06.26 21:51 kimberlyhebert786

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
22.06.26 21:51 kimberlyhebert786

I invested in bitcoin trading After losing $78.4 USDT) linked to a romance fraud scam worth of cryptocurrency through an online investment platform and later discovered it was a scam. After extensive research for recovery options, I contacted CAPITAL CRYPTO RECOVER based on positive client reviews and recommendations. Their professional security team guided me through the recovery process using advanced technology, and I was able to recover my lost cryptocurrency successfully. I am truly grateful for their support and assistance during such a difficult experience. I will advise you to contact CAPITAL CRYPTO RECOVER helped me recover my funds. For anyone facing similar issues, Website: https://recovercapital.wixsite.com/capital-crypto-rec-1 Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text Number: +1 (336) 390-6684
24.06.26 01:25 Fraddy Pual

I never thought it would happen to me—but I lost $256,100 in Bitcoin through a shady investment deal. I was shattered, panicked, and convinced my savings were gone forever. Just when I was about to give up, I stumbled upon reviews for FUNDSRETRIEVER, a cyber recovery team with a solid reputation. I decided to give it a shot, and to my absolute shock, they recovered every single cent in record time. Working with them was a lifesaver. If you've been tricked by fake investment platforms, don't lose hope—FUNDSRETRIEVER can help. Contact them here: Email: [email protected] | WhatsApp: +1603512144 8| Telegram: @Fundsretriever
24.06.26 01:27 Fraddy Pual

I never thought it would happen to me—but I lost $256,100 in Bitcoin through a shady investment deal. I was shattered, panicked, and convinced my savings were gone forever. Just when I was about to give up, I stumbled upon reviews for FUNDSRETRIEVER, a cyber recovery team with a solid reputation. I decided to give it a shot, and to my absolute shock, they recovered every single cent in record time. Working with them was a lifesaver. If you've been tricked by fake investment platforms, don't lose hope—FUNDSRETRIEVER can help. Contact them here: Email: [email protected] | WhatsApp: +16035121448 | Telegram: @Fundsretriever
24.06.26 01:28 Fraddy Pual

I never thought it would happen to me—but I lost $256,100 in Bitcoin through a shady investment deal. I was shattered, panicked, and convinced my savings were gone forever. Just when I was about to give up, I stumbled upon reviews for FUNDSRETRIEVER, a cyber recovery team with a solid reputation. I decided to give it a shot, and to my absolute shock, they recovered every single cent in record time. Working with them was a lifesaver. If you've been tricked by fake investment platforms, don't lose hope—FUNDSRETRIEVER can help. Contact them here: Email: [email protected] | WhatsApp: +16035121448 | Telegram: @Fundsretriever.
24.06.26 01:58 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
24.06.26 01:58 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
24.06.26 14:16 Universina da Mota

Becoming a victim of an investment scam is never anyone's intention it often happens because fraudsters exploit trust and a lack of awareness. I would like to express my sincere gratitude to the dedicated team at ResQpro for their professionalism and commitment to helping victims of online investment fraud. Their efforts in assisting individuals with the recovery of stolen assets and holding scammers accountable are truly commendable. If you need assistance or would like to learn more, you can contact them through: Email: [email protected] Alternative Email: [email protected] Telegram: @ResQprofirm WhatsApp: +1 (985) 296-9146
24.06.26 14:21 Elizabeth Thompson

If you believe you have been the victim of an investment scam, it is important to act promptly and gather all relevant information. Keep records of transaction receipts, wallet addresses, communication logs, account details, and any other evidence related to the incident. Providing accurate documentation can help investigators, financial institutions, legal professionals, or recovery specialists review your case and determine what options may be available. Be cautious of anyone who guarantees the recovery of lost funds or requests large upfront payments. For additional information, you may contact: Email: [email protected] Telegram: @ResQprofirm WhatsApp: +1 (985) 296-9146
24.06.26 15:33 Júlia Castro

If you have fallen victim to an investment scam, it is important to act quickly and gather all available evidence related to the incident. This may include transaction records, wallet addresses, screenshots of conversations, emails, account details, and any information connected to the individuals or entities involved. Having complete documentation can help professionals assess your situation and explore possible recovery options. Always exercise caution when seeking assistance and carefully verify the credentials of any service provider before proceeding. For further information, you may contact: Email: [email protected] Telegram: @ResQprofirm WhatsApp: +1 (985) 296-9146
24.06.26 22:01 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
24.06.26 22:01 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
25.06.26 21:13 Emilie Safi

A fraudulent investment scheme operated by BTCMining.limited functions as a fake return scam. In this setup, scammers lure victims with false promises of high returns. Through manipulative tactics, they gain individuals' trust and convince them to invest, ultimately leading to financial loss. If you have ever faced a cyber threat or fallen victim to an online crypto scam and need to reach the authorities, I recommend contacting [email protected], [email protected], WhatsApp +19852969146, telegram @resqprofirm. They are a legitimate team that helps victims of online crypto scams using advanced tools.
25.06.26 21:25 Emilie Safi

So I ended up losing $38,000 to this platform. At first, they kept asking me to put in more money so I could get into my portfolio. I did that, but then they wouldn’t let me withdraw anything—just kept asking for more deposits. It got way too suspicious, so I stopped. I found this company called ResQProfirm on Google and told them what happened. They got in touch, asked me to walk them through everything, and I gave them all the proof I had. They did an amazing job tracking down my money and getting it back. Big thanks to them at [email protected] and on WhatsApp at +19852969146. Please be careful out there and always research before investing.
26.06.26 01:04 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
26.06.26 01:04 robertalfred175

CRYPTO SCAM RECOVERY SUCCESSFUL – A TESTIMONIAL OF LOST PASSWORD TO YOUR DIGITAL WALLET BACK. My name is Robert Alfred, Am from Australia. I’m sharing my experience in the hope that it helps others who have been victims of crypto scams. A few months ago, I fell victim to a fraudulent crypto investment scheme linked to a broker company. I had invested heavily during a time when Bitcoin prices were rising, thinking it was a good opportunity. Unfortunately, I was scammed out of $120,000 AUD and the broker denied me access to my digital wallet and assets. It was a devastating experience that caused many sleepless nights. Crypto scams are increasingly common and often involve fake trading platforms, phishing attacks, and misleading investment opportunities. In my desperation, a friend from the crypto community recommended Capital Crypto Recovery Service, known for helping victims recover lost or stolen funds. After doing some research and reading multiple positive reviews, I reached out to Capital Crypto Recovery. I provided all the necessary information—wallet addresses, transaction history, and communication logs. Their expert team responded immediately and began investigating. Using advanced blockchain tracking techniques, they were able to trace the stolen Dogecoin, identify the scammer’s wallet, and coordinate with relevant authorities to freeze the funds before they could be moved. Incredibly, within 24 hours, Capital Crypto Recovery successfully recovered the majority of my stolen crypto assets. I was beyond relieved and truly grateful. Their professionalism, transparency, and constant communication throughout the process gave me hope during a very difficult time. If you’ve been a victim of a crypto scam, I highly recommend them with full confidence contacting: Email: [email protected] Telegram: @Capitalcryptorecover Contact: [email protected] Call/Text: +1 (336) 390-6684 Website: https://recovercapital.wixsite.com/capital-crypto-rec-1
26.06.26 02:48 Miriam Rocha

I trusted this platform with $120,000 of my hard-earned money. Then they started asking for more deposits just so I could access my own portfolio. I paid, but every withdrawal request was denied. They kept pushing for more money. I finally stopped it just felt wrong. Desperate, I found ResQProfirm on Google. They didn't just hear me out; they truly listened. I shared all my proof, and they launched an investigation. Thanks to their hard work, they tracked and returned my funds. From the bottom of my heart, thank you to [email protected] and their WhatsApp +19852969146. Please stay safe and always verify a platform before investing
26.06.26 02:52 Miško Bakić

I got my $232,000 refund thanks to [email protected] and WhatsApp +19852969146. Highly recommended for anyone in a similar situation.
26.06.26 02:56 Asunción Herrera

A recovery of $48,330 was facilitated by [email protected]. Individuals who have experienced financial fraud may consider contacting this service.
26.06.26 15:05 Riley Stephens

If withdrawals keep getting denied, stay calm. I went through the same, and this firm helped me recover everything. Their assistance was outstanding. Contact: [ResQProFirm @Gmail|•|com], Telegram: ResQprofirm, WhatsApp: <+198> <5296> <9146>.
26.06.26 15:09 Antonio Riley

Withdrawal troubles shouldn’t stress you out. I faced a similar problem, and this firm stepped in and recovered my funds. Their support truly mattered. Contact them: [[email protected], ResQprofirm @aol.com], Telegram: ResQprofirm, WhatsApp: +19852969146.