ml-kernel

[![NPM version][npm-image]][npm-url]
[![build status][travis-image]][travis-url]
[![npm download][download-image]][download-url]

A factory for kernel functions.

Installation

$ npm i ml-kernel

Usage

$3

This function can be called with a matrix of input vectors.
and optional landmarks. If no landmark is provided, the input vectors will be used.

Available kernels:

- linear - Linear kernel
- gaussian or rbf - Gaussian (radial basis function) kernel
- polynomial or poly - Polynomial kernel
- exponential - Exponential kernel
- laplacian - Laplacian kernel
- anova - ANOVA kernel
- rational - Rational Quadratic kernel
- multiquadratic - Multiquadratic kernel
- cauchy - Cauchy kernel
- histogram or min - Histogram Intersection kernel
- sigmoid or `mlp' - Sigmoid (hyperbolic tangent) kernel

$3

This function can be called with a matrix of input vectors and optional landmarks.
If no landmark is provided, the input vectors will be used.
The function returns a kernel matrix of feature space vectors.

License

MIT

[npm-image]: https://img.shields.io/npm/v/ml-kernel.svg?style=flat-square
[npm-url]: https://npmjs.org/package/ml-kernel
[travis-image]: https://img.shields.io/travis/mljs/kernel/master.svg?style=flat-square
[travis-url]: https://travis-ci.org/mljs/kernel
[download-image]: https://img.shields.io/npm/dm/ml-kernel.svg?style=flat-square
[download-url]: https://npmjs.org/package/ml-kernel