Multivariate Pattern Analysis in Python

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# mvpa2.kernels.libsvm

PyMVPA LibSVM-based kernels

These kernels do not currently have the ability to run the calculations, so they are not translateable to other kernel types. They are implemented solely to standardize the interface between other kernel machines.

Classes

`Kernel`(*args, **kwargs) | Abstract class which calculates a kernel function between datasets Each instance has an internal representation self._k which might be of a different form depending on the intended use.
`LSKernel`(*args, **kwargs) | A Kernel object which dictates how LibSVM will calculate the kernel ..
`LinearLSKernel`(*args, **kwargs) | A simple Linear kernel: K(a,b) = a*b.T ..
`Parameter`(default[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter.
`PolyLSKernel`(**kwargs) | Polynomial kernel: K(a,b) = (gamma*a*b.T + coef0)**degree ..
`RbfLSKernel`(**kwargs) | Radial Basis Function kernel (aka Gaussian): K(a,b) = exp(-gamma*||a-b||**2) ..
`SigmoidLSKernel`(**kwargs) | Sigmoid kernel: K(a,b) = tanh(gamma*a*b.T + coef0) ..

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