Package Exports

ml-kernel

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Readme

ml-kernel

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
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

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.

License

MIT