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#Weka.classifiers.meta Classes and Interfaces - 17 results found.
Name | Description | Type | Package | Framework |
AdaBoostM1 | Class for boosting a nominal class classifier using the Adaboost M1 method. | Class | weka.classifiers.meta | Weka |
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AdditiveRegression | Meta classifier that enhances the performance of a regression base classifier. | Class | weka.classifiers.meta | Weka |
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AttributeSelectedClassifier | Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier. | Class | weka.classifiers.meta | Weka |
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Bagging | Class for bagging a classifier to reduce variance. | Class | weka.classifiers.meta | Weka |
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ClassificationViaRegression | Class for doing classification using regression methods. | Class | weka.classifiers.meta | Weka |
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CostSensitiveClassifier | A metaclassifier that makes its base classifier cost-sensitive. | Class | weka.classifiers.meta | Weka |
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CVParameterSelection | Class for performing parameter selection by cross-validation for any classifier. | Class | weka.classifiers.meta | Weka |
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MultiClassClassifier | A metaclassifier for handling multi-class datasets with 2-class classifiers. | Class | weka.classifiers.meta | Weka |
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MultiClassClassifierUpdateable | A metaclassifier for handling multi-class datasets with 2-class classifiers. | Class | weka.classifiers.meta | Weka |
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MultiScheme | Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data. | Class | weka.classifiers.meta | Weka |
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RandomCommittee | Class for building an ensemble of randomizable base classifiers. | Class | weka.classifiers.meta | Weka |
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RandomizableFilteredClassifier | Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. | Class | weka.classifiers.meta | Weka |
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RandomSubSpace | This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity. | Class | weka.classifiers.meta | Weka |
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RegressionByDiscretization | A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized. | Class | weka.classifiers.meta | Weka |
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Stacking | Combines several classifiers using the stacking method. | Class | weka.classifiers.meta | Weka |
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Vote | Class for combining classifiers. | Class | weka.classifiers.meta | Weka |
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WeightedInstancesHandlerWrapper | Generic wrapper around any classifier to enable weighted instances support. | Class | weka.classifiers.meta | Weka |