Multivariate Pattern Analysis in Python

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# mvpa2.clfs.gpr

Gaussian Process Regression (GPR).

Functions

`NLAcholesky`(a) | Cholesky decomposition.
`NLAsolve`(a, b) | Solve a linear matrix equation, or system of linear scalar equations.
`Ndiag`(v[, k]) | Extract a diagonal or construct a diagonal array.
`Ndot`(a, b[, out]) | Dot product of two arrays.
`SLcho_solve`(c_and_lower, b[, overwrite_b, ...]) | Solve the linear equations A x = b, given the Cholesky factorization of A.
`SLcholesky`(a[, lower, overwrite_a, check_finite]) | Compute the Cholesky decomposition of a matrix.
`accepts_dataset_as_samples`(fx) | Decorator to extract samples from Datasets.
`array`(object[, dtype, copy, order, subok, ndmin]) | Create an array.
`asarray`(a[, dtype, order]) | Convert the input to an array.

Classes

`Classifier`([space]) | Abstract classifier class to be inherited by all classifiers ..
`ConditionalAttribute`([enabled]) | Simple container intended to conditionally store the value ..
`Dataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.
`GPR`([kernel]) | Gaussian Process Regression (GPR).
`GPRLinearWeights`(clf[, force_train]) | `SensitivityAnalyzer` that reports the weights GPR trained
`GeneralizedLinearKernel`(*args, **kwargs) | The linear kernel class.
`LinearKernel`(*args, **kwargs) | 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.
`Sensitivity`(clf[, force_train]) | Sensitivities of features for a given Classifier.
`SquaredExponentialKernel`([length_scale, sigma_f]) | The Squared Exponential kernel class.

Exceptions

`Classifier`([space]) | Abstract classifier class to be inherited by all classifiers ..
`ConditionalAttribute`([enabled]) | Simple container intended to conditionally store the value ..
`Dataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.
`GPR`([kernel]) | Gaussian Process Regression (GPR).
`GPRLinearWeights`(clf[, force_train]) | `SensitivityAnalyzer` that reports the weights GPR trained
`GeneralizedLinearKernel`(*args, **kwargs) | The linear kernel class.
`LinearKernel`(*args, **kwargs) | 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.
`Sensitivity`(clf[, force_train]) | Sensitivities of features for a given Classifier.
`SquaredExponentialKernel`([length_scale, sigma_f]) | The Squared Exponential kernel class.

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