|
Class Summary |
| ClassifiedDataset |
Pairs a dataset and a classifier, for easy inspection
of the actions of a classifier. |
| ClassifiedDataset.ExplanationViewer |
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| CrossValidatedDataset |
View result of some sort of train/test experiment. |
| CrossValSplitter<T> |
Split into k separate disjoint folds, then return k train/test splits
where each train set is the union of k-1 folds, and the test set
is the k-th fold. |
| Evaluation |
Stores some detailed results of evaluating a classifier on data. |
| Evaluation.ConfusionMatrixViewer |
|
| Evaluation.ElevenPointPrecisionViewer |
|
| Evaluation.Matrix |
|
| Evaluation.PropertyViewer |
|
| Evaluation.ROCViewer |
|
| EvaluationGroup |
A group of related evaluations. |
| Expt |
Simple experiment on a classifier. |
| FixedTestSetSplitter<T> |
Provides exactly one 'split', between the entire set given, and a fixed
designated test set. |
| LeaveOneOutSplitter<T> |
Do N-fold cross-validation, where N is the number of different
subpopulations. |
| RandomSplitter<T> |
Split into one train, one test partition. |
| SimpleRandomSplitter<T> |
Split into one train, one test partition. |
| StrataSorter |
Helper class for splitting up iterators over Examples, by class. |
| StratifiedCrossValSplitter |
Works with datasets of binary examples. |
| SubpopSorter<T> |
Helper class for splitting up iterators over Instances |
| SubsamplingCrossValSplitter<T> |
Variant of cross-validation in which not all training data is used. |
| Tester |
Test a classifier, in a number of ways. |
| WebmasterSplitter<T> |
A complicated splitter that stratifies samples according to an
arbitrary "profile" property, and restricts train/test splits to
not cross boundaries defined by "user" and "request" properties. |