@ai-on-browser/data-analysis-models
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Data analysis model package without any dependencies
63 lines (62 loc) • 1.48 kB
TypeScript
/**
* Variational Gaussian Mixture Model
*/
export default class VBGMM {
/**
* @param {number} a Tuning parameter
* @param {number} b Tuning parameter
* @param {number} k Initial number of clusters
*/
constructor(a: number, b: number, k: number);
_a0: number;
_b0: number;
_k: number;
/**
* Means
* @type {Matrix}
*/
get means(): Matrix;
/**
* Covariances
* @type {Matrix[]}
*/
get covs(): Matrix[];
/**
* Effectivity
* @type {boolean[]}
*/
get effectivity(): boolean[];
/**
* Initialize model.
* @param {Array<Array<number>>} datas Training data
*/
init(datas: Array<Array<number>>): void;
_x: Matrix<number[]>;
_m0: Matrix<number>;
_w0: Matrix<number>;
_nu0: number;
_r: any;
_digamma(z: any): any;
_bernoulli(n: any): number;
/**
* Fit model.
*/
fit(): void;
_p: Matrix<number>;
_m: Matrix<number>;
_w: any[];
_nu: Matrix<number>;
/**
* Returns probability of the datas.
* @param {Array<Array<number>>} data Sample data
* @returns {Matrix} Predicted values
*/
probability(data: Array<Array<number>>): Matrix;
/**
* Returns predicted categories.
* @param {Array<Array<number>>} data Sample data
* @returns {number[]} Predicted values
*/
predict(data: Array<Array<number>>): number[];
}
import Matrix from '../util/matrix.js';