Class RFE

Initialize recursive feature elimination

:Parameters:
    sensitivity_analyzer : FeaturewiseDatasetMeasure object
    transfer_error : TransferError object
        used to compute the transfer error of a classifier based on a
        certain feature set on the test dataset.
        NOTE: If sensitivity analyzer is based on the same
        classifier as transfer_error is using, make sure you
        initialize transfer_error with train=False, otherwise
        it would train classifier twice without any necessity.
    feature_selector : Functor
        Given a sensitivity map it has to return the ids of those
        features that should be kept.
    bestdetector : Functor
        Given a list of error values it has to return a boolean that
        signals whether the latest error value is the total minimum.
    stopping_criterion : Functor
        Given a list of error values it has to return whether the
        criterion is fulfilled.
    train_clf : bool
        Flag whether the classifier in `transfer_error` should be
        trained before computing the error. In general this is
        required, but if the `sensitivity_analyzer` and
        `transfer_error` share and make use of the same classifier it
        can be switched off to save CPU cycles. Default `None` checks
        if sensitivity_analyzer is based on a classifier and doesn't train
        if so.
    update_sensitivity : bool
        If False the sensitivity map is only computed once and reused
        for each iteration. Otherwise the senstitivities are
        recomputed at each selection step.

Overrides: object.__init__

Proceed and select the features recursively eliminating less important ones.

Returns a tuple of two new datasets with the feature subset of dataset that had the lowest transfer error of all tested sets until the stopping criterion was reached. The first dataset is the feature subset of the training data and the second the selection of the test dataset.

Parameters:

• dataset (Dataset) - used to compute sensitivity maps and train a classifier to determine the transfer error
• testdataset (Dataset) - used to test the trained classifer to determine the transfer error

Overrides: base.FeatureSelection.__call__