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See:
Description
Interface Summary | |
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Classifier | Classes implementing this interface must be able to classify items represented by feature vectors. |
Class Summary | |
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ClassTrain | Classifies a list of files, training the classifier on each error if the true class is provided. |
ExternalClassifier | A proxy that provides a trainable classifier by communicating with an external (non-Java) program. |
MetaClassifier | A meta classifier combines several layers of classifiers. |
MoonClassifier | A proxy to the MoonFilter classifier written by Christian Siefkes. |
MultiBinaryClassifier | This classifier converts an multi-class classification task into a several binary (two-class) classification task. |
OneAgainstTheRestClassifier | This classifier converts an multi-class classification task into a several binary (two-class) classification task. |
Prediction | A prediction, wrapping the predicted class and the probability of the prediction. |
PredictionComparator | A comparison function that compares
Prediction s based on their
probabilities. |
PredictionDistribution | A distribution over the classes predicted by a classifier. |
Probability | Wraps a probability. |
Reranker | Reranks the predictions in a distribution by multiplying the probabilities of each of them with a bias, if specified for the type of the prediction. |
TextFilter | A text filter provides a simple API for classifying text files. |
TieClassifier | A tie classifier combines several layers of classifiers. |
TrainableClassifier | Classifiers extending this abstract class must provide a training mechanism
by implementing the TrainableClassifier.doTrain(FeatureVector, String, ContextMap)
method. |
Tuner | This class provides support for iterative training, also called TUNE (Train-until-no-errors) training. |
This package provides functionality for classification of texts and feature vectors.
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