import { TransformerBase } from '../base';
import { Params } from '../base/estimator';
export interface BernoulliRBMOptions {
    nComponents?: number;
    learningRate?: number;
    batchSize?: number;
    nIter?: number;
    randomState?: number;
}
export declare class BernoulliRBM extends TransformerBase {
    private nComponents;
    private learningRate;
    private batchSize;
    private nIter;
    private randomState?;
    /** Serializable RNG state (Park–Miller LCG); `null` when unseeded. */
    private rngState;
    private components;
    private interceptHidden;
    private interceptVisible;
    constructor(options?: BernoulliRBMOptions);
    getParams(): Params;
    private nextRandom;
    private initParams;
    private hiddenProb;
    private visibleProb;
    private cdStep;
    fit(X: number[][]): void;
    partialFit(X: number[][]): void;
    transform(X: number[][]): number[][];
    fitTransform(X: number[][]): number[][];
    gibbs(V: number[][]): number[][];
}