Class CrossValidatedTransferError

:Parameters:
  transerror: TransferError instance
    Provides the classifier used for cross-validation.
  splitter: Splitter | None
    Used to split the dataset for cross-validation folds. By
    convention the first dataset in the tuple returned by the
    splitter is used to train the provided classifier. If the
    first element is 'None' no training is performed. The second
    dataset is used to generate predictions with the (trained)
    classifier. If `None` (default) an instance of
    :class:`~mvpa.datasets.splitters.NoneSplitter` is used.
  combiner: Functor | 'mean'
    Used to aggregate the error values of all cross-validation
    folds. If 'mean' (default) the grand mean of the transfer
    errors is computed.
  expose_testdataset: bool
   In the proper pipeline, classifier must not know anything
   about testing data, but in some cases it might lead only
   to marginal harm, thus migth wanted to be enabled (provide
   testdataset for RFE to determine stopping point).
  harvest_attribs: list of basestr
    What attributes of call to store and return within
    harvested state variable
  copy_attribs: None | basestr
    Force copying values of attributes on harvesting
  **kwargs:
    All additional arguments are passed to the
    :class:`~mvpa.measures.base.DatasetMeasure` base class.

Parameters:

• transformer, Functor - This functor is called in __call__() to perform a final processing step on the to be returned dataset measure. If None, nothing is called
• null_dist, instance, of, distribution, estimator - The estimated distribution is used to assign a probability for a certain value of the computed measure.

Overrides: object.__init__

results

Value:

StateVariable(enabled= False, doc= """Store individual results in the state""")

splits

Value:

StateVariable(enabled= False, doc= """Store the actual splits of the d ata. Can be memory expensive""")

transerrors

Value:

StateVariable(enabled= False, doc= """Store copies of transerrors at e ach step. If enabled - operates on clones of transerror, but for the last split origin al transerror is used""")

confusion

Value:

StateVariable(enabled= False, doc= """Store total confusion matrix (if available)""")

training_confusion

Value:

StateVariable(enabled= False, doc= """Store total training confusion m atrix (if available)""")

samples_error

Value:

StateVariable(enabled= False, doc= "Per sample errors.")

splitter

Value:

property(fget= lambda self: self.__splitter, doc= "Access to the Split ter instance.")

transerror

Value:

property(fget= lambda self: self.__transerror, doc= "Access to the Tra nsferError instance.")

combiner

Value:

property(fget= lambda self: self.__combiner, doc= "Access to the confi gured combiner.")