/** @import {InputType} from "../index.js" */
/** @import {Metric} from "../metrics/index.js" */
/** @import {ParametersTSNE} from "./index.js" */
/**
 * t-SNE (t-Distributed Stochastic Neighbor Embedding)
 *
 * A nonlinear dimensionality reduction technique particularly well-suited
 * for visualizing high-dimensional data in 2D or 3D. Preserves local
 * structure while revealing global patterns.
 *
 * @class
 * @template {InputType} T
 * @extends DR<T, ParametersTSNE>
 * @category Dimensionality Reduction
 * @see {@link https://lvdmaaten.github.io/tsne/|t-SNE Paper}
 * @see {@link UMAP} for faster alternative with similar results
 *
 * @example
 * import * as druid from "@saehrimnir/druidjs";
 *
 * const X = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]];
 * const tsne = new druid.TSNE(X, {
 *     perplexity: 30,
 *     epsilon: 10,
 *     d: 2,
 *     seed: 42
 * });
 *
 * const Y = tsne.transform(500); // 500 iterations
 * // [[x1, y1], [x2, y2], [x3, y3]]
 */
export class TSNE<T extends InputType> extends DR<T, ParametersTSNE> {
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersTSNE>} [parameters]
   * @returns {T}
   */
  static transform<T_1 extends InputType>(X: T_1, parameters?: Partial<ParametersTSNE>): T_1;
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersTSNE>} [parameters]
   * @returns {Generator<T, T, void>}
   */
  static generator<T_1 extends InputType>(
    X: T_1,
    parameters?: Partial<ParametersTSNE>,
  ): Generator<T_1, T_1, void>;
  /**
   * @template {InputType} T
   * @param {T} X
   * @param {Partial<ParametersTSNE>} [parameters]
   * @returns {Promise<T>}
   */
  static transform_async<T_1 extends InputType>(
    X: T_1,
    parameters?: Partial<ParametersTSNE>,
  ): Promise<T_1>;
  /**
   * @param {T} X - The high-dimensional data.
   * @param {Partial<ParametersTSNE>} [parameters] - Object containing parameterization of the DR method.
   */
  constructor(X: T, parameters?: Partial<ParametersTSNE>);
  _iter: number;
  init(): this;
  _ystep: Matrix | undefined;
  _gains: Matrix | undefined;
  _P: Matrix | undefined;
  /**
   * @param {number} [iterations=500] - Number of iterations. Default is `500`
   * @returns {T} The projection.
   */
  transform(iterations?: number): T;
  /**
   * @param {number} [iterations=500] - Number of iterations. Default is `500`
   * @returns {Generator<T, T, void>} - The projection.
   */
  generator(iterations?: number): Generator<T, T, void>;
  /**
   * Performs a optimization step
   *
   * @private
   * @returns {Matrix}
   */
  private next;
}
import type { InputType } from "../index.js";
import type { ParametersTSNE } from "./index.js";
import { DR } from "./DR.js";
import { Matrix } from "../matrix/index.js";
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