ml-basic/dist/types/optimizers/rms-prop.d.ts

Lightweight, zero dependency, machine learning library

import Matrix from "../lib/matrix";
import BatchGradientDescent from "./batch-gradient-descent";
export type RMSPropParams = {
    /**
     * @default 0.01
     */
    learningRate?: number;
    /**
     * @default 0
     */
    clipping?: number;
    /**
     * @default 4
     */
    batchSize?: number;
    /**
     * @default 0.9
     */
    beta1?: number;
    /**
     * @default 1e-8
     */
    epsilon?: number;
};
export default class RMSProp extends BatchGradientDescent {
    name: string;
    beta1: number;
    epsilon: number;
    private v?;
    constructor({ learningRate, clipping, batchSize, beta1, epsilon }?: RMSPropParams);
    step(input: Matrix, gradient: Matrix, callback: (input: Matrix, gradient: Matrix) => void): void;
}