import * as tf from '../backend/adapter';
/** Lets downstream code work identically across estimators regardless of how each exposes cluster representatives. */
export interface ClusterRepresentations {
    centroids_?: tf.Tensor2D | null;
    /**
     * Library-defined: scikit-learn exposes no equivalent attribute.
     * `-1` if that cluster has no assigned samples; ties on distance resolve to the lowest sample index.
     */
    medoid_indices_?: Int32Array | null;
    /**
     * Library-defined: scikit-learn exposes no equivalent attribute.
     * Map key is cluster id; value is the exemplar sample index. Ties resolve to the lowest sample index.
     */
    exemplar_indices_?: Map<number, number> | null;
}
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