/** @import { InputType } from "../index.js" */
/** @import { ParametersXMeans } from "./index.js" */
/**
 * @typedef SplitResult
 * @property {number} index - Index of the cluster being split
 * @property {number} bic_parent - BIC score of the parent cluster
 * @property {number} bic_children - BIC score of the split children
 * @property {number[][]} child_clusters - Clusters after splitting
 * @property {Float64Array[]} child_centroids - Centroids of child clusters
 */
/**
 * @typedef CandidateResult
 * @property {KMeans} kmeans - The KMeans instance for this K
 * @property {number} score - BIC score
 */
/**
 * X-Means Clustering
 *
 * An extension of K-Means that automatically determines the number of clusters (K)
 * using the Bayesian Information Criterion (BIC).
 *
 * @class
 * @extends Clustering<ParametersXMeans>
 * @category Clustering
 */
export class XMeans extends Clustering<ParametersXMeans> {
  /**
   * XMeans clustering algorithm that automatically determines the optimal number of clusters.
   *
   * X-Means extends K-Means by starting with a minimum number of clusters and iteratively
   * splitting clusters to improve the Bayesian Information Criterion (BIC).
   *
   * Algorithm:
   * 1. Start with K_min clusters using KMeans
   * 2. For each cluster, try splitting it into 2 sub-clusters
   * 3. If BIC improves after splitting, keep the split
   * 4. Run KMeans again with all (old + new) centroids
   * 5. Repeat until K_max is reached or no more improvements
   *
   * @param {InputType} points - The data points to cluster
   * @param {Partial<ParametersXMeans>} [parameters={}] - Configuration parameters
   * @see {@link https://www.cs.cmu.edu/~dpelleg/download/xmeans.pdf}
   * @see {@link https://github.com/annoviko/pyclustering/blob/master/pyclustering/cluster/xmeans.py}
   * @see {@link https://github.com/haifengl/smile/blob/master/core/src/main/java/smile/clustering/XMeans.java}
   */
  constructor(points: InputType, parameters?: Partial<ParametersXMeans>);
  _randomizer: Randomizer;
  /** @type {KMeans | null} */
  _best_kmeans: KMeans | null;
  /**
   * Run the XMeans algorithm
   *
   * @private
   */
  private _run;
  /**
   * Select the best candidate based on BIC score
   *
   * @private
   * @param {Map<number, CandidateResult>} candidates
   * @returns {KMeans}
   */
  private _select_best_candidate;
  /**
   * Calculate Bayesian Information Criterion for a set of clusters.
   *
   * Uses Kass's formula for BIC calculation:
   * BIC(θ) = L(D) - 0.5 * p * ln(N)
   *
   * Where:
   * - L(D) is the log-likelihood of the data
   * - p is the number of free parameters: (K-1) + D*K + 1
   * - N is the total number of points
   *
   * @private
   * @param {number[][]} clusters - Array of clusters with point indices
   * @param {Float64Array[]} centroids - Array of centroids
   * @returns {number} BIC score (higher is better)
   */
  private _bic;
  /**
   * Get the computed clusters
   *
   * @returns {number[][]} Array of clusters, each containing indices of points
   */
  get_clusters(): number[][];
  /** @returns {number[]} The cluster list */
  get_cluster_list(): number[];
  /**
   * Get the final centroids
   *
   * @returns {Float64Array[]} Array of centroids
   */
  get centroids(): Float64Array[];
  /**
   * Get the optimal number of clusters found
   *
   * @returns {number} The number of clusters
   */
  get k(): number;
}
export type SplitResult = {
  /**
   * - Index of the cluster being split
   */
  index: number;
  /**
   * - BIC score of the parent cluster
   */
  bic_parent: number;
  /**
   * - BIC score of the split children
   */
  bic_children: number;
  /**
   * - Clusters after splitting
   */
  child_clusters: number[][];
  /**
   * - Centroids of child clusters
   */
  child_centroids: Float64Array[];
};
export type CandidateResult = {
  /**
   * - The KMeans instance for this K
   */
  kmeans: KMeans;
  /**
   * - BIC score
   */
  score: number;
};
import type { ParametersXMeans } from "./index.js";
import { Clustering } from "./Clustering.js";
import { Randomizer } from "../util/index.js";
import { KMeans } from "./KMeans.js";
import type { InputType } from "../index.js";
//# sourceMappingURL=XMeans.d.ts.map