ml-basic/dist/types/lib/functions.d.ts

Lightweight, zero dependency, machine learning library

import Matrix from "./matrix";
export declare abstract class LossFunction {
    abstract name: string;
    abstract mean(output: Matrix, target: Matrix): number;
    abstract derivative(output: Matrix, target: Matrix): Matrix;
    serialize(): string;
}
export declare class SquaredLoss extends LossFunction {
    name: string;
    mean(output: Matrix, target: Matrix): number;
    derivative(output: Matrix, target: Matrix): Matrix;
}
export declare class CrossEntropyLoss extends LossFunction {
    name: string;
    mean(output: Matrix, target: Matrix): number;
    derivative(output: Matrix, target: Matrix): Matrix;
}
export declare abstract class Activator {
    abstract name: string;
    abstract activate(n: number): number;
    abstract deactivate(n: number): number;
    serialize(): string;
}
export declare class Sigmoid extends Activator {
    name: string;
    activate(n: number): number;
    deactivate(n: number): number;
}
export declare class TanH extends Activator {
    name: string;
    activate(n: number): number;
    deactivate(n: number): number;
}
export declare class Elu extends Activator {
    name: string;
    alpha: number;
    constructor(alpha?: number);
    activate: (n: number) => number;
    deactivate: (n: number) => number;
}
export declare class Relu extends Elu {
    name: string;
    constructor(alpha?: number);
    activate: (n: number) => number;
    deactivate: (n: number) => number;
}
export declare class SoftPlus extends Activator {
    name: string;
    activate(n: number): number;
    deactivate(n: number): number;
}