/** @import {InputType} from "../index.js" */ /** @import {ParametersMDS} from "./index.js" */ /** @import {EigenArgs} from "../linear_algebra/index.js" */ /** * Classical Multidimensional Scaling (MDS) * * A linear dimensionality reduction technique that seeks to preserve the * pairwise distances between points as much as possible in the lower-dimensional * space. * * @class * @template {InputType} T * @extends DR * @category Dimensionality Reduction * @see {@link PCA} for another linear alternative */ export class MDS extends DR { /** * @template {InputType} T * @param {T} X * @param {Partial} [parameters] * @returns {T} */ static transform(X: T_1, parameters?: Partial): T_1; /** * @template {InputType} T * @param {T} X * @param {Partial} [parameters] * @returns {Generator} */ static generator( X: T_1, parameters?: Partial, ): Generator; /** * @template {InputType} T * @param {T} X * @param {Partial} [parameters] * @returns {Promise} */ static transform_async( X: T_1, parameters?: Partial, ): Promise; /** * Classical MDS. * * @param {T} X - The high-dimensional data. * @param {Partial} [parameters] - Object containing parameterization of the DR method. */ constructor(X: T, parameters?: Partial); /** * Transforms the inputdata `X` to dimensionality `d`. * * @returns {Generator} A generator yielding the intermediate steps of the projection. */ generator(): Generator; /** * Transforms the inputdata `X` to dimensionality `d`. * * @returns {T} */ transform(): T; _d_X: Matrix | undefined; /** @returns {number} - The stress of the projection. */ stress(): number; } import type { InputType } from "../index.js"; import type { ParametersMDS } from "./index.js"; import { DR } from "./DR.js"; import { Matrix } from "../matrix/index.js"; //# sourceMappingURL=MDS.d.ts.map