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Multivariate Pattern Analysis in Python |
Utility class to compute the transfer error of classifiers.
The comprehensive API documentation for this module, including all technical details, is available in the Epydoc-generated API reference for mvpa.clfs.transerror (for developers).
Bases: mvpa.misc.state.ClassWithCollections
Compute (or return) some error of a (trained) classifier on a dataset.
Initialization.
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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 ClassifierError documentation.
Full API documentation of ClassifierError in module mvpa.clfs.transerror.
Bases: mvpa.clfs.transerror.ClassifierError
For a given classifier report an error based on internally computed error measure (given by some ConfusionMatrix stored in some state variable of Classifier).
This way we can perform feature selection taking as the error criterion either learning error, or transfer to splits error in the case of SplitClassifier
Initialization.
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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 ConfusionBasedError documentation.
Full API documentation of ConfusionBasedError in module mvpa.clfs.transerror.
Bases: mvpa.clfs.transerror.SummaryStatistics
Class to contain information and display confusion matrix.
Implementation of the SummaryStatistics in the case of classification problem. Actual computation of confusion matrix is delayed until all data is acquired (to figure out complete set of labels). If testing data doesn’t have a complete set of labels, but you like to include all labels, provide them as a parameter to the constructor.
Confusion matrix provides a set of performance statistics (use asstring(description=True) for the description of abbreviations), as well ROC curve (http://en.wikipedia.org/wiki/ROC_curve) plotting and analysis (AUC) in the limited set of problems: binary, multiclass 1-vs-all.
Initialize ConfusionMatrix with optional list of labels
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‘Pretty print’ the matrix
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Provide presentation of confusion matrix in image
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Return type: | (fig, im, cb) – figure, imshow, colorbar |
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 ConfusionMatrix documentation.
Full API documentation of ConfusionMatrix in module mvpa.clfs.transerror.
Bases: object
Generic class for ROC curve computation and plotting
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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 ROCCurve documentation.
Full API documentation of ROCCurve in module mvpa.clfs.transerror.
Bases: mvpa.clfs.transerror.SummaryStatistics
Class to contain information and display on regression results.
Initialize RegressionStatistics
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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 RegressionStatistics documentation.
Full API documentation of RegressionStatistics in module mvpa.clfs.transerror.
Bases: object
Basic class to collect targets/predictions and report summary statistics
It takes care about collecting the sets, which are just tuples (targets, predictions, values). While ‘computing’ the matrix, all sets are considered together. Children of the class are responsible for computation and display.
Initialize SummaryStatistics
targets or predictions cannot be provided alone (ie targets without predictions)
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‘Pretty print’ the matrix
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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 SummaryStatistics documentation.
Full API documentation of SummaryStatistics in module mvpa.clfs.transerror.
Bases: mvpa.clfs.transerror.ClassifierError
Compute the transfer error of a (trained) classifier on a dataset.
The actual error value is computed using a customizable error function. Optionally the classifier can be trained by passing an additional training dataset to the __call__() method.
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 TransferError documentation.
Full API documentation of TransferError in module mvpa.clfs.transerror.