Source code for topologic.embedding.clustering.gaussian_mixture_model

# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.

import numpy as np
from sklearn.mixture import GaussianMixture

[docs]def gaussian_mixture_model( embedding: np.ndarray, num_clusters: int = 1, seed: int = None, ) -> np.ndarray: """ Performs gaussian mixture model clustering on the feature_matrix. :param numpy.ndarray embedding: An n x d feature matrix; it is assumed that the d features are ordered :param int num_clusters: How many clusters to look at between min_clusters and max_clusters, default 1 :param Optional[int] seed: The seed for numpy random, default None :return: The cluster labels for each vector in the given embedding. The vector at index n in the embedding will have the label at index n in this returned array :rtype: np.ndarray """ np.random.seed(seed) classifier = GaussianMixture( n_components=num_clusters, covariance_type='spherical' ) predictions = classifier.predict(embedding) predictions = np.array([int(i) for i in predictions]) return predictions