# ml-kernel

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A factory for kernel functions.

## Installation

`$ npm i ml-kernel`

## Usage

### new Kernel(type, options)

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](https://github.com/mljs/kernel-gaussian)
- `polynomial` or `poly` - [Polynomial kernel](https://github.com/mljs/kernel-polynomial)
- `exponential` - [Exponential kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#exponential)
- `laplacian` - [Laplacian kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#laplacian)
- `anova` - [ANOVA kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#anova)
- `rational` - [Rational Quadratic kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#rational)
- `multiquadratic` - [Multiquadratic kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#multiquadric)
- `cauchy` - [Cauchy kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#cauchy)
- `histogram` or `min` - [Histogram Intersection kernel](http://crsouza.com/2010/03/kernel-functions-for-machine-learning-applications/#histogram)
- `sigmoid` or `mlp` - [Sigmoid (hyperbolic tangent) kernel](https://github.com/mljs/kernel-sigmoid)

### kernel.compute(inputs, landmarks)

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.

## Example

```js
import { Kernel } from 'ml-kernel';

const kernel = new Kernel('gaussian', { sigma: 1 });
const result = kernel.compute([
  [1, 2],
  [3, 4],
]);
// result is an ml-matrix Matrix instance
```

## License

[MIT](./LICENSE)

[npm-image]: https://img.shields.io/npm/v/ml-kernel.svg?style=flat-square
[npm-url]: https://npmjs.org/package/ml-kernel
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[ci-url]: https://github.com/mljs/kernel/actions/workflows/nodejs.yml
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[download-url]: https://npmjs.org/package/ml-kernel