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Multivariate Pattern Analysis in Python |
Cross-validate a classifier on a dataset
The comprehensive API documentation for this module, including all technical details, is available in the Epydoc-generated API reference for mvpa.algorithms.cvtranserror (for developers).
Bases: mvpa.measures.base.DatasetMeasure, mvpa.misc.state.Harvestable
Cross validate a classifier on datasets generated by a splitter from a source dataset.
Arbitrary performance/error values can be computed by specifying an error function (used to compute an error value for each cross-validation fold) and a combiner function that aggregates all computed error values across cross-validation folds.
Cheap initialization.
Parameters: |
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See also
Derived classes might provide additional methods via their base classes. Please refer to the list of base classes (if it exists) at the begining of the CrossValidatedTransferError documentation.
Full API documentation of CrossValidatedTransferError in module mvpa.algorithms.cvtranserror.