clustering-tfjs/dist/clustering/spectral_optimization.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';
import type { SpectralClusteringParams } from './types';
/**
 * Configuration for parameter optimization
 */
interface OptimizationConfig {
    gamma: number;
    metric: 'calinski-harabasz' | 'davies-bouldin' | 'silhouette';
    attempts: number;
    useValidation: boolean;
}
/**
 * Result of optimization
 */
interface OptimizationResult {
    labels: number[];
    config: OptimizationConfig;
    score?: number;
}
/**
 * Performs validation-based optimization for spectral clustering.
 * Tries multiple k-means initializations and selects the best based on validation score.
 */
export declare function validationBasedOptimization(embedding: tf.Tensor2D, nClusters: number, metric: 'calinski-harabasz' | 'davies-bouldin' | 'silhouette', attempts: number, randomState?: number): Promise<OptimizationResult>;
/**
 * Performs intensive parameter sweep for difficult clustering problems.
 * Tests multiple gamma values and validation configurations.
 */
export declare function intensiveParameterSweep(X: tf.Tensor2D, params: SpectralClusteringParams, computeEmbeddingFromAffinity: (affinityMatrix: tf.Tensor2D) => Promise<tf.Tensor2D>, computeAffinityMatrix: (X: tf.Tensor2D, params: SpectralClusteringParams) => tf.Tensor2D): Promise<OptimizationResult>;
export {};
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