/** @import {InputType} from "../index.js" */
/** @import {ParametersLSP} from "./index.js" */
/**
 * Least Square Projection (LSP)
 *
 * A dimensionality reduction technique that uses a small set of control points
 * (projected with MDS) to define the projection for the rest of the data
 * using a Laplacian-based optimization.
 *
 * @class
 * @template {InputType} T
 * @extends DR<T, ParametersLSP>
 * @category Dimensionality Reduction
 */
export class LSP<T extends InputType> extends DR<T, ParametersLSP> {
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersLSP>} [parameters]
   * @returns {T}
   */
  static transform<T_1 extends InputType>(X: T_1, parameters?: Partial<ParametersLSP>): T_1;
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersLSP>} [parameters]
   * @returns {Generator<T, T, void>}
   */
  static generator<T_1 extends InputType>(
    X: T_1,
    parameters?: Partial<ParametersLSP>,
  ): Generator<T_1, T_1, void>;
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersLSP>} [parameters]
   * @returns {Promise<T>}
   */
  static transform_async<T_1 extends InputType>(
    X: T_1,
    parameters?: Partial<ParametersLSP>,
  ): Promise<T_1>;
  /**
   * Least Squares Projection.
   *
   * @param {T} X - The high-dimensional data.
   * @param {Partial<ParametersLSP>} [parameters] - Object containing parameterization of the DR method.
   * @see {@link https://ieeexplore.ieee.org/document/4378370}
   */
  constructor(X: T, parameters?: Partial<ParametersLSP>);
  /**
   * @returns {LSP<T>}
   */
  init(): LSP<T>;
  _A: Matrix | undefined;
  _b: Matrix | undefined;
  /**
   * Computes the projection.
   *
   * @returns {T} Returns the projection.
   */
  transform(): T;
}
import type { InputType } from "../index.js";
import type { ParametersLSP } from "./index.js";
import { DR } from "./DR.js";
import { Matrix } from "../matrix/index.js";
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