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. |
EnsureFloat() | Ensure that an input (or several inputs) are of a data type ‘float’. |
EnsureListOf(dtype) | Ensure that an input is a list of a particular data type |
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[, constraints, ro, index, ...]) | 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 |
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. |
EnsureFloat() | Ensure that an input (or several inputs) are of a data type ‘float’. |
EnsureListOf(dtype) | Ensure that an input is a list of a particular data type |
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[, constraints, ro, index, ...]) | 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 |
SquaredExponentialKernel([length_scale, sigma_f]) | The Squared Exponential kernel class. |