Class DriftDetectionMethodClassifier

    • Field Detail

      • baseLearnerOption

        public ClassOption baseLearnerOption
      • driftDetectionMethodOption

        public ClassOption driftDetectionMethodOption
      • newclassifier

        protected Classifier newclassifier
      • newClassifierReset

        protected boolean newClassifierReset
      • ddmLevel

        protected int ddmLevel
      • changeDetected

        protected int changeDetected
      • warningDetected

        protected int warningDetected
    • Constructor Detail

      • DriftDetectionMethodClassifier

        public DriftDetectionMethodClassifier()
    • Method Detail

      • isWarningDetected

        public boolean isWarningDetected()
      • isChangeDetected

        public boolean isChangeDetected()
      • resetLearningImpl

        public void resetLearningImpl()
        Description copied from class: AbstractClassifier
        Resets this classifier. It must be similar to starting a new classifier from scratch.

        The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. Note that this will produce compiler errors if not overridden.
        Specified by:
        resetLearningImpl in class AbstractClassifier
      • trainOnInstanceImpl

        public void trainOnInstanceImpl​(Instance inst)
        Description copied from class: AbstractClassifier
        Trains this classifier incrementally using the given instance.

        The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. Note that this will produce compiler errors if not overridden.
        Specified by:
        trainOnInstanceImpl in class AbstractClassifier
        Parameters:
        inst - the instance to be used for training
      • getVotesForInstance

        public double[] getVotesForInstance​(Instance inst)
        Description copied from interface: Classifier
        Predicts the class memberships for a given instance. If an instance is unclassified, the returned array elements must be all zero.
        Specified by:
        getVotesForInstance in interface Classifier
        Specified by:
        getVotesForInstance in class AbstractClassifier
        Parameters:
        inst - the instance to be classified
        Returns:
        an array containing the estimated membership probabilities of the test instance in each class
      • isRandomizable

        public boolean isRandomizable()
        Description copied from interface: Learner
        Gets whether this learner needs a random seed. Examples of methods that needs a random seed are bagging and boosting.
        Specified by:
        isRandomizable in interface Learner<Example<Instance>>
        Returns:
        true if the learner needs a random seed.
      • getModelDescription

        public void getModelDescription​(StringBuilder out,
                                        int indent)
        Description copied from class: AbstractClassifier
        Returns a string representation of the model.
        Specified by:
        getModelDescription in class AbstractClassifier
        Parameters:
        out - the stringbuilder to add the description
        indent - the number of characters to indent
      • getModelMeasurementsImpl

        protected Measurement[] getModelMeasurementsImpl()
        Description copied from class: AbstractClassifier
        Gets the current measurements of this classifier.

        The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. Note that this will produce compiler errors if not overridden.
        Specified by:
        getModelMeasurementsImpl in class AbstractClassifier
        Returns:
        an array of measurements to be used in evaluation tasks