mvpa2.kernels.npΒΆ
Kernels for Gaussian Process Regression and Classification.
Functions
| squared_euclidean_distance(data1[, data2, ...]) | Compute weighted euclidean distance matrix between two datasets. |
Classes
| ConditionalAttribute([enabled]) | Simple container intended to conditionally store the value .. |
| 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. |
| NumpyKernel(*args, **kwargs) | A Kernel object with internal representation as a 2d numpy array .. |
| Parameter(default[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter. |
| 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 K(a,b) = exp(-||a-b||**2/sigma) .. |
| SquaredExponentialKernel([length_scale, sigma_f]) | The Squared Exponential kernel class. |
Exceptions
| ConditionalAttribute([enabled]) | Simple container intended to conditionally store the value .. |
| 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. |
| NumpyKernel(*args, **kwargs) | A Kernel object with internal representation as a 2d numpy array .. |
| Parameter(default[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter. |
| 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 K(a,b) = exp(-||a-b||**2/sigma) .. |
| SquaredExponentialKernel([length_scale, sigma_f]) | The Squared Exponential kernel class. |
