Multivariate Pattern Analysis in Python

# mvpa2.kernels.np

Kernels for Gaussian Process Regression and Classification.

Classes

`ConstantKernel`(*args, **kwargs) | The constant kernel class.
`ExponentialKernel`(*args, **kwargs) | The Exponential kernel class.
`GeneralizedLinearKernel`(*args, **kwargs) | The linear kernel class.
`LinearKernel`(*args, **kwargs) | Simple linear kernel: K(a,b) = a*b.T
`Matern_3_2Kernel`([length_scale, sigma_f, …]) | The Matern kernel class for the case ni=3/2 or ni=5/2.
`Matern_5_2Kernel`(**kwargs) | The Matern kernel class for the case ni=5/2.
`PolyKernel`(*args, **kwargs) | Polynomial kernel: K(a,b) = (gamma*a*b.T+coef0)**degree
`RationalQuadraticKernel`([length_scale, …]) | The Rational Quadratic (RQ) kernel class.
`RbfKernel`(*args, **kwargs) | Radial basis function (aka Gausian, aka ) kernel
`SquaredExponentialKernel`([length_scale, sigma_f]) | The Squared Exponential kernel class.