@ai-on-browser/data-analysis-models/lib/model/laplacian_eigenmaps.d.ts

Data analysis model package without any dependencies

/**
 * Laplacian eigenmaps
 */
export default class LaplacianEigenmaps {
    /**
     * @param {number} rd Reduced dimension
     * @param {'rbf' | 'knn' | { name: 'rbf', sigma?: number, k?: number } | { name: 'knn', k?: number }} [affinity] Affinity type name
     * @param {'unnormalized' | 'normalized'} [laplacian] Normalized laplacian matrix or not
     */
    constructor(rd: number, affinity?: "rbf" | "knn" | {
        name: "rbf";
        sigma?: number;
        k?: number;
    } | {
        name: "knn";
        k?: number;
    }, laplacian?: "unnormalized" | "normalized");
    _rd: number;
    _affinity: {
        name: "rbf";
        sigma?: number;
        k?: number;
    } | {
        name: "knn";
        k?: number;
    } | {
        name: "rbf" | "knn";
    };
    _laplacian: "unnormalized" | "normalized";
    /**
     * Returns reduced datas.
     * @param {Array<Array<number>>} x Training data
     * @returns {Array<Array<number>>} Predicted values
     */
    predict(x: Array<Array<number>>): Array<Array<number>>;
    _ev: Matrix<number>;
}
import Matrix from '../util/matrix.js';