Hierarchical clustering algorithm is unstructured. The data into a connectivity matrix, such as derived from This can be a connectivity matrix itself or a callable that transforms Samples following a given structure of the data. connectivity array-like or callable, default=NoneĬonnectivity matrix. Used to cache the output of the computation of the tree.īy default, no caching is done. ![]() memory str or object with the joblib.Memory interface, default=None ![]() If “precomputed”, a distance matrix (instead of a similarity matrix) If linkage is “ward”, only “euclidean” is accepted. affinity str or callable, default=’euclidean’ It must be None ifĭistance_threshold is not None. Parameters n_clusters int or None, default=2 Recursively merges pair of clusters of sample data uses linkage distance. ![]() AgglomerativeClustering ( n_clusters = 2, *, affinity = 'euclidean', memory = None, connectivity = None, compute_full_tree = 'auto', linkage = 'ward', distance_threshold = None, compute_distances = False ) ¶
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