Multivariate Pattern Analysis in Python

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# mvpa2.testing.clfs

Provides `clfs` dictionary with instances of all available classifiers.

Functions

`accepts_dataset_as_samples`(fx) | Decorator to extract samples from Datasets.

Classes

`Classifier`([space]) | Abstract classifier class to be inherited by all classifiers ..
`Dataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.
`FeaturewiseMeasure`([null_dist]) | A per-feature-measure computed from a `Dataset` (base class).
`Less1Classifier`(**kwargs) | Dummy classifier which reports +1 class if abs value of max less than 1 ..
`LinearCSVMC`([C]) | C-SVM classifier using linear kernel.
`LinearNuSVMC`([nu]) | Nu-SVM classifier using linear kernel.
`LinearSVMKernel` | A simple Linear kernel: K(a,b) = a*b.T ..
`RbfCSVMC`([C]) | C-SVM classifier using a radial basis function kernel See documentation of `AttributesCollector` for more information ..
`RbfNuSVMC`([nu]) | Nu-SVM classifier using a radial basis function kernel See documentation of `AttributesCollector` for more information ..
`RbfSVMKernel` | Radial Basis Function kernel (aka Gaussian): K(a,b) = exp(-gamma*||a-b||**2) ..
`SMLR`(**kwargs) | Sparse Multinomial Logistic Regression `Classifier`.
`SVM`(**kwargs) | Support Vector Machine Classifier.
`SameSignClassifier`(**kwargs) | Dummy classifier which reports +1 class if both features have the same sign, -1 otherwise ..
`SillySensitivityAnalyzer`([mult]) | Simple one which just returns xrange[-N/2, N/2], where N is the number of features ..
`kNN`([k, dfx, voting]) | k-Nearest-Neighbour classifier.

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