mvpa2.clfs.transerrorΒΆ
Utility class to compute the transfer error of classifiers.
Functions
Classes
BayesConfusionHypothesis([alpha, ...]) |
Bayesian hypothesis testing on confusion matrices. |
ClassifierError(clf[, labels, train]) |
Compute (or return) some error of a (trained) classifier on a dataset. |
Confusion([attr, labels, add_confusion_obj]) |
Compute a confusion matrix from predictions and targets (Node interface) |
ConfusionBasedError(clf[, labels, ...]) |
For a given classifier report an error based on internally computed error measure (given by some ConfusionMatrix stored in some conditional attribute of Classifier). |
ConfusionMatrix([labels, labels_map]) |
Class to contain information and display confusion matrix. |
ConfusionMatrixError([labels]) |
Compute confusion matrix as an “error function” |
ROCCurve(labels[, sets]) |
Generic class for ROC curve computation and plotting |
RegressionStatistics(**kwargs) |
Class to contain information and display on regression results. |
SummaryStatistics([targets, predictions, ...]) |
Basic class to collect targets/predictions and report summary statistics |
Exceptions
BayesConfusionHypothesis([alpha, ...]) |
Bayesian hypothesis testing on confusion matrices. |
ClassifierError(clf[, labels, train]) |
Compute (or return) some error of a (trained) classifier on a dataset. |
Confusion([attr, labels, add_confusion_obj]) |
Compute a confusion matrix from predictions and targets (Node interface) |
ConfusionBasedError(clf[, labels, ...]) |
For a given classifier report an error based on internally computed error measure (given by some ConfusionMatrix stored in some conditional attribute of Classifier). |
ConfusionMatrix([labels, labels_map]) |
Class to contain information and display confusion matrix. |
ConfusionMatrixError([labels]) |
Compute confusion matrix as an “error function” |
ROCCurve(labels[, sets]) |
Generic class for ROC curve computation and plotting |
RegressionStatistics(**kwargs) |
Class to contain information and display on regression results. |
SummaryStatistics([targets, predictions, ...]) |
Basic class to collect targets/predictions and report summary statistics |



