all_points_membership_vectors

cuml.cluster.hdbscan.all_points_membership_vectors(clusterer, int batch_size=4096)

Predict soft cluster membership vectors for all points in the original dataset the clusterer was trained on. This function is more efficient by making use of the fact that all points are already in the condensed tree, and processing in bulk.

Parameters:

clustererHDBSCAN

A clustering object that has been fit to the data and had prediction_data=True set.

batch_sizeint, optional, default=min(4096, n_rows)

Lowers memory requirement by computing distance-based membership in smaller batches of points in the training data. For example, a batch size of 1,000 computes distance based memberships for 1,000 points at a time. The default batch size is 4,096.

Returns:

membership_vectorsarray (n_samples, n_clusters)

The probability that point i of the original dataset is a member of cluster j is in membership_vectors[i, j].