Uses of Package
weka.classifiers
Package
Description
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ClassDescriptionAbstract classifier.Classifier interface.Class for storing and manipulating a misclassification cost matrix.Class for evaluating machine learning models.Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple classifiers.Abstract utility class for handling settings common to meta classifiers that use a single base learner.Interface for classifiers that can be converted to Java source.
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ClassDescriptionAbstract classifier.Classifier interface.Updateable classifiers can implement this if they wish to be informed at the end of the training stream.Interface to incremental classification models that can learn using one instance at a time.
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ClassDescriptionClassifier interface.Interface for numeric prediction schemes that can output conditional density estimates.Class for storing and manipulating a misclassification cost matrix.Interface for numeric prediction schemes that can output prediction intervals.Interface for classifiers that can be converted to Java source.
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ClassDescriptionAbstract classifier.Classifier interface.Interface for numeric prediction schemes that can output conditional density estimates.Interface for numeric prediction schemes that can output prediction intervals.Interface for classifiers that can induce models of growing complexity one step at a time.Abstract utility class for handling settings common to randomizable classifiers.Updateable classifiers can implement this if they wish to be informed at the end of the training stream.Interface to incremental classification models that can learn using one instance at a time.
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ClassDescriptionAbstract classifier.Classifier interface.Abstract utility class for handling settings common to meta classifiers that use a single base learner.Interface to incremental classification models that can learn using one instance at a time.
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ClassDescriptionAbstract classifier.Classifier interface.Interface for numeric prediction schemes that can output conditional density estimates.Class for storing and manipulating a misclassification cost matrix.Interface for numeric prediction schemes that can output prediction intervals.Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.Interface for classifiers that can induce models of growing complexity one step at a time.Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple classifiers.Abstract utility class for handling settings common to randomizable classifiers.Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers based on a given random number seed.Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single base learner.Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple classifiers based on a given random number seed.Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.Abstract utility class for handling settings common to meta classifiers that use a single base learner.Interface for classifiers that can be converted to Java source.Interface to incremental classification models that can learn using one instance at a time.
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ClassDescriptionAbstract classifier.Classifier interface.Abstract utility class for handling settings common to meta classifiers that use a single base learner.
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ClassDescriptionAbstract classifier.Classifier interface.Interface for classifiers that can be converted to Java source.
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ClassDescriptionAbstract classifier.Classifier interface.Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single base learner.Abstract utility class for handling settings common to meta classifiers that use a single base learner.Interface for classifiers that can be converted to Java source.Interface to incremental classification models that can learn using one instance at a time.
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ClassDescriptionClassifier interface.Class for storing and manipulating a misclassification cost matrix.Class for evaluating machine learning models.
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