clustering-tfjs/dist/utils/component_indicators.d.ts

High-performance TypeScript clustering algorithms (K-Means, Spectral, Agglomerative) with TensorFlow.js acceleration and scikit-learn compatibility

import * as tf from '../tf-adapter';
/**
 * Creates component indicator features for disconnected graphs.
 *
 * For a graph with k connected components, this creates indicator features
 * where each feature has a constant value for all nodes in that component.
 * This mimics the behavior of sklearn's shift-invert eigenvectors.
 *
 * @param componentLabels - Array indicating which component each node belongs to
 * @param numComponents - Total number of components detected
 * @param maxIndicators - Maximum number of indicator vectors to create (usually nClusters)
 * @returns Component indicator matrix (n_samples x min(numComponents, maxIndicators))
 */
export declare function createComponentIndicators(componentLabels: Int32Array, numComponents: number, maxIndicators: number): tf.Tensor2D;
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