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mvpa.clfs.gprΒΆ
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) | Dot product of two arrays. |
| SLcho_solve(clow, b) | Solve a previously factored symmetric system of equations. |
| SLcholesky(a[, lower, overwrite_a]) | 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(**kwargs[, space]) | Abstract classifier class to be inherited by all classifiers .. |
| ConditionalAttribute(*args, **kwargs[, enabled]) | Simple container intended to conditionally store the value |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| GPR(**kwargs[, kernel]) | Gaussian Process Regression (GPR). |
| GPRLinearWeights(clf, **kwargs[, 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, **kwargs[, ro, index, ...]) | This class shall serve as a representation of a parameter. |
| Sensitivity(clf, **kwargs[, force_train]) | Sensitivities of features for a given Classifier. |
| SquaredExponentialKernel(**kwargs[, ...]) | The Squared Exponential kernel class. |
Exceptions
| Classifier(**kwargs[, space]) | Abstract classifier class to be inherited by all classifiers .. |
| ConditionalAttribute(*args, **kwargs[, enabled]) | Simple container intended to conditionally store the value |
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
| GPR(**kwargs[, kernel]) | Gaussian Process Regression (GPR). |
| GPRLinearWeights(clf, **kwargs[, 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, **kwargs[, ro, index, ...]) | This class shall serve as a representation of a parameter. |
| Sensitivity(clf, **kwargs[, force_train]) | Sensitivities of features for a given Classifier. |
| SquaredExponentialKernel(**kwargs[, ...]) | The Squared Exponential kernel class. |
