/** @import {InputType} from "../index.js" */
/** @import {ParametersLDA} from "./index.js" */
/** @import {EigenArgs} from "../linear_algebra/index.js" */
/**
 * Linear Discriminant Analysis (LDA)
 *
 * A supervised dimensionality reduction technique that finds the axes that
 * maximize the separation between multiple classes.
 *
 * @class
 * @template {InputType} T
 * @extends DR<T, ParametersLDA>
 * @category Dimensionality Reduction
 */
export class LDA<T extends InputType> extends DR<T, ParametersLDA> {
  /**
   * @template {InputType} T
   * @template {{ seed?: number }} Para
   * @param {T} X
   * @param {Para} parameters
   * @returns {T}
   */
  static transform<
    T_1 extends InputType,
    Para extends {
      seed?: number;
    },
  >(X: T_1, parameters: Para): T_1;
  /**
   * @template {InputType} T
   * @template {{ seed?: number }} Para
   * @param {T} X
   * @param {Para} parameters
   * @returns {Generator<T, T, void>}
   */
  static generator<
    T_1 extends InputType,
    Para extends {
      seed?: number;
    },
  >(X: T_1, parameters: Para): Generator<T_1, T_1, void>;
  /**
   * @template {InputType} T
   * @template {{ seed?: number }} Para
   * @param {T} X
   * @param {Para} parameters
   * @returns {Promise<T>}
   */
  static transform_async<
    T_1 extends InputType,
    Para extends {
      seed?: number;
    },
  >(X: T_1, parameters: Para): Promise<T_1>;
  /**
   * Linear Discriminant Analysis.
   *
   * @param {T} X - The high-dimensional data.
   * @param {Partial<ParametersLDA> & { labels: any[] | Float64Array }} parameters - Object containing parameterization of the DR method.
   * @see {@link https://onlinelibrary.wiley.com/doi/10.1111/j.1469-1809.1936.tb02137.x}
   */
  constructor(
    X: T,
    parameters: Partial<ParametersLDA> & {
      labels: any[] | Float64Array;
    },
  );
  /**
   * Transforms the inputdata `X` to dimensionality `d`.
   *
   * @returns {Generator<T, T, void>} A generator yielding the intermediate steps of the projection.
   */
  generator(): Generator<T, T, void>;
  /**
   * Transforms the inputdata `X` to dimensionality `d`.
   *
   * @returns {T} - The projected data.
   */
  transform(): T;
}
import type { InputType } from "../index.js";
import type { ParametersLDA } from "./index.js";
import { DR } from "./DR.js";
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