Expected Outputs

CoreSGClusterer exposes current artifacts for the most recent fitted k. Its internal core_sg_ object keeps lower-level fit-time artifacts for advanced inspection.

After CoreSGClusterer.fit(…)

After CoreSGClusterer.fit(X, k=...):

labels_

Cluster labels for the most recent extracted k.

probabilities_

HDBSCAN-style membership strengths.

cluster_persistence_

Persistence values for selected clusters.

condensed_tree_

Wrapped condensed tree for the current extraction.

single_linkage_tree_

Wrapped single linkage tree for the current extraction.

minimum_spanning_tree_

Wrapped minimum spanning tree for the current extraction.

k_

The current extracted k.

k_max_

The validated reusable capacity.

core_sg_

Internal reusable Core-SG object. Most users do not need to call it directly.

Advanced internal artifacts

The internal core_sg_ object stores:

support_graph_

Reusable Core-SG support graph.

metric_edges_

Original metric distances for support edges.

core_distances_

Matrix of core-distance candidates. get_core_distance(k) selects column k - 1.

distance_matrix_

Dense pairwise distance matrix for algorithm="core-sg" only.

anti_hubs_

Selected anti-hub indices for algorithm="score-sg" only.

labels_k_max_

Labels saved for the reference fit at k_max.

probabilities_k_max_

Probabilities saved for the reference fit at k_max.

cluster_persistence_k_max_

Cluster persistence saved for the reference fit at k_max.

condensed_tree_k_max_

Wrapped condensed tree saved at k_max.

single_linkage_tree_k_max_

Wrapped single linkage tree saved at k_max.

minimum_spanning_tree_k_max_

Wrapped minimum spanning tree saved at k_max.