Hierarchy For All Packages

Package Hierarchies:

• es.upm.fi.cig.multictbnc,
• es.upm.fi.cig.multictbnc.classification,
• es.upm.fi.cig.multictbnc.conceptdriftdetection,
• es.upm.fi.cig.multictbnc.data.reader,
• es.upm.fi.cig.multictbnc.data.representation,
• es.upm.fi.cig.multictbnc.data.writer,
• es.upm.fi.cig.multictbnc.exceptions,
• es.upm.fi.cig.multictbnc.experiments,
• es.upm.fi.cig.multictbnc.experiments.implementationsexperiments,
• es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.featurestreamexperiments,
• es.upm.fi.cig.multictbnc.fss,
• es.upm.fi.cig.multictbnc.gui,
• es.upm.fi.cig.multictbnc.learning,
• es.upm.fi.cig.multictbnc.learning.parameters,
• es.upm.fi.cig.multictbnc.learning.parameters.bn,
• es.upm.fi.cig.multictbnc.learning.parameters.ctbn,
• es.upm.fi.cig.multictbnc.learning.structure,
• es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC,
• es.upm.fi.cig.multictbnc.learning.structure.constraints,
• es.upm.fi.cig.multictbnc.learning.structure.constraints.BN,
• es.upm.fi.cig.multictbnc.learning.structure.constraints.CTBNC,
• es.upm.fi.cig.multictbnc.learning.structure.hybrid,
• es.upm.fi.cig.multictbnc.learning.structure.hybrid.hillclimbing,
• es.upm.fi.cig.multictbnc.learning.structure.hybrid.PC,
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing,
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation,
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores,
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.bn,
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn,
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.tabusearch,
• es.upm.fi.cig.multictbnc.models,
• es.upm.fi.cig.multictbnc.models.submodels,
• es.upm.fi.cig.multictbnc.nodes,
• es.upm.fi.cig.multictbnc.performance,
• es.upm.fi.cig.multictbnc.sampling,
• es.upm.fi.cig.multictbnc.services,
• es.upm.fi.cig.multictbnc.tasks,
• es.upm.fi.cig.multictbnc.util,
• es.upm.fi.cig.multictbnc.writers.classification,
• es.upm.fi.cig.multictbnc.writers.performance

Class Hierarchy

• java.lang.Object
  • java.util.AbstractCollection<E> (implements java.util.Collection<E>)
    • java.util.AbstractList<E> (implements java.util.List<E>)
      • java.util.AbstractSequentialList<E>
        • java.util.LinkedList<E> (implements java.lang.Cloneable, java.util.Deque<E>, java.util.List<E>, java.io.Serializable)
          • es.upm.fi.cig.multictbnc.data.representation.SlidingWindow<T>
  • es.upm.fi.cig.multictbnc.data.reader.AbstractCSVReader (implements es.upm.fi.cig.multictbnc.data.reader.DatasetReader)
    • es.upm.fi.cig.multictbnc.data.reader.MultipleCSVReader
    • es.upm.fi.cig.multictbnc.data.reader.SingleCSVReader
  • es.upm.fi.cig.multictbnc.experiments.AbstractExperiment (implements es.upm.fi.cig.multictbnc.experiments.Experiment)
    • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.LearningStreamExperiment
    • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.ModelComparisonExperiment
    • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.StructureLearningAlgorithmsComparisonExperiment
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.AbstractLikelihood
    • es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.bn.BNLogLikelihood (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.bn.BNScoreFunction)
    • es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn.CTBNConditionalLogLikelihood (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn.CTBNScoreFunction)
    • es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn.CTBNLogLikelihood (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn.CTBNScoreFunction)
  • es.upm.fi.cig.multictbnc.nodes.AbstractNode (implements es.upm.fi.cig.multictbnc.nodes.Node)
    • es.upm.fi.cig.multictbnc.nodes.DiscreteStateNode
      • es.upm.fi.cig.multictbnc.nodes.CIMNode
      • es.upm.fi.cig.multictbnc.nodes.CPTNode
  • es.upm.fi.cig.multictbnc.models.AbstractPGM<NodeType> (implements es.upm.fi.cig.multictbnc.models.PGM<NodeType>)
    • es.upm.fi.cig.multictbnc.models.BN<NodeType>
    • es.upm.fi.cig.multictbnc.models.CTBN<NodeType>
    • es.upm.fi.cig.multictbnc.models.MultiCTBNC<NodeTypeBN,NodeTypeCTBN> (implements es.upm.fi.cig.multictbnc.classification.Classifier)
      • es.upm.fi.cig.multictbnc.models.submodels.DAG_maxK_MultiCTBNC<NodeTypeBN,NodeTypeCTBN>
      • es.upm.fi.cig.multictbnc.models.submodels.Empty_digraph_MultiCTBNC<NodeTypeBN,NodeTypeCTBN>
      • es.upm.fi.cig.multictbnc.models.submodels.Empty_maxK_MultiCTBNC<NodeTypeBN,NodeTypeCTBN>
      • es.upm.fi.cig.multictbnc.models.submodels.MultiCTNBC<NodeTypeBN,NodeTypeCTBN>
  • es.upm.fi.cig.multictbnc.learning.structure.constraints.AbstractStructureConstraints (implements es.upm.fi.cig.multictbnc.learning.structure.constraints.StructureConstraints)
    • es.upm.fi.cig.multictbnc.learning.structure.constraints.BN.DAG
    • es.upm.fi.cig.multictbnc.learning.structure.constraints.CTBNC.Digraph
    • es.upm.fi.cig.multictbnc.learning.structure.constraints.BN.EmptyBN
    • es.upm.fi.cig.multictbnc.learning.structure.constraints.CTBNC.MaxKCTBNC
    • es.upm.fi.cig.multictbnc.learning.structure.constraints.CTBNC.NaiveBayes
  • javafx.application.Application
    • es.upm.fi.cig.multictbnc.Main
    • es.upm.fi.cig.multictbnc.sampling.MainDataStreamSampling.MainDataStreamSamplingFX
    • es.upm.fi.cig.multictbnc.sampling.MainFeatureStreamSampling.MainFeatureStreamSamplingFX
  • es.upm.fi.cig.multictbnc.conceptdriftdetection.AverageLocalLogLikelihood (implements es.upm.fi.cig.multictbnc.conceptdriftdetection.ConceptDriftScore)
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.bn.BNBayesianScore (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.bn.BNScoreFunction)
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation.BNHillClimbing (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation.HillClimbingImplementation)
    • es.upm.fi.cig.multictbnc.learning.structure.hybrid.hillclimbing.BNHillClimbingHybridAlgorithm
    • es.upm.fi.cig.multictbnc.learning.structure.optimisation.tabusearch.BNTabuSearch
  • es.upm.fi.cig.multictbnc.learning.structure.hybrid.BNHybridStructureLearningAlgorithm (implements es.upm.fi.cig.multictbnc.learning.structure.StructureLearningAlgorithm)
  • es.upm.fi.cig.multictbnc.learning.BNLearningAlgorithms
  • es.upm.fi.cig.multictbnc.learning.parameters.bn.BNParameterLearningAlgorithm (implements es.upm.fi.cig.multictbnc.learning.parameters.ParameterLearningAlgorithm)
    • es.upm.fi.cig.multictbnc.learning.parameters.bn.BNBayesianEstimation
    • es.upm.fi.cig.multictbnc.learning.parameters.bn.BNMaximumLikelihoodEstimation
  • es.upm.fi.cig.multictbnc.learning.parameters.bn.BNParameterLearningAlgorithmFactory
  • es.upm.fi.cig.multictbnc.learning.parameters.bn.BNSufficientStatistics (implements es.upm.fi.cig.multictbnc.learning.parameters.SufficientStatistics)
  • es.upm.fi.cig.multictbnc.classification.ClassifierFactory
  • java.awt.Component (implements java.awt.image.ImageObserver, java.awt.MenuContainer, java.io.Serializable)
    • java.awt.Container
      • java.awt.Window (implements javax.accessibility.Accessible)
        • java.awt.Frame (implements java.awt.MenuContainer)
          • javax.swing.JFrame (implements javax.accessibility.Accessible, javax.swing.RootPaneContainer, javax.swing.WindowConstants)
            • org.jfree.chart.ui.ApplicationFrame (implements java.awt.event.WindowListener)
              • es.upm.fi.cig.multictbnc.gui.TimeSeriesChart
              • es.upm.fi.cig.multictbnc.gui.XYLineChart
  • es.upm.fi.cig.multictbnc.conceptdriftdetection.ConceptDriftAdaptiveMethod
    • es.upm.fi.cig.multictbnc.conceptdriftdetection.ConceptDriftGloballyAdaptiveMethod
    • es.upm.fi.cig.multictbnc.conceptdriftdetection.ConceptDriftLocallyAdaptiveMethod
  • es.upm.fi.cig.multictbnc.gui.Controller
  • es.upm.fi.cig.multictbnc.util.ControllerUtil
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn.CTBNBayesianScore (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn.CTBNScoreFunction)
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation.CTBNHillClimbing (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation.HillClimbingImplementation)
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation.CTBNHillClimbingIndividual (implements es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation.HillClimbingImplementation)
    • es.upm.fi.cig.multictbnc.learning.structure.hybrid.hillclimbing.CTBNHillClimbingHybridAlgorithm
    • es.upm.fi.cig.multictbnc.learning.structure.optimisation.tabusearch.CTBNTabuSearchIndividual
  • es.upm.fi.cig.multictbnc.learning.structure.hybrid.CTBNHybridStructureLearningAlgorithm (implements es.upm.fi.cig.multictbnc.learning.structure.StructureLearningAlgorithm)
  • es.upm.fi.cig.multictbnc.learning.CTBNLearningAlgorithms
  • es.upm.fi.cig.multictbnc.learning.parameters.ctbn.CTBNParameterLearningAlgorithm (implements es.upm.fi.cig.multictbnc.learning.parameters.ParameterLearningAlgorithm)
    • es.upm.fi.cig.multictbnc.learning.parameters.ctbn.CTBNBayesianEstimation
    • es.upm.fi.cig.multictbnc.learning.parameters.ctbn.CTBNMaximumLikelihoodEstimation
  • es.upm.fi.cig.multictbnc.learning.parameters.ctbn.CTBNParameterLearningAlgorithmFactory
  • es.upm.fi.cig.multictbnc.learning.parameters.ctbn.CTBNSufficientStatistics (implements es.upm.fi.cig.multictbnc.learning.parameters.SufficientStatistics)
  • es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.CTPC (implements es.upm.fi.cig.multictbnc.learning.structure.StructureLearningAlgorithm)
    • es.upm.fi.cig.multictbnc.learning.structure.hybrid.PC.CTPCHybridAlgorithm
    • es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.MarkovBlanketCTPC
      • es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.OnlineMarkovBlanketCTPC
  • es.upm.fi.cig.multictbnc.sampling.DataSampler
  • es.upm.fi.cig.multictbnc.data.representation.Dataset
  • es.upm.fi.cig.multictbnc.data.reader.DatasetReaderFactory
  • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.DataStreamExperiment
  • es.upm.fi.cig.multictbnc.data.reader.DataStreamMultipleCSVReader
  • es.upm.fi.cig.multictbnc.experiments.ExperimentFactory
  • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.FeatureStreamExperiment
  • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.featurestreamexperiments.FeatureStreamExperimentFactory
  • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.featurestreamexperiments.FeatureStreamImplementationExperiment
    • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.featurestreamexperiments.FeatureStreamAsStaticDatasetExperiment
    • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.featurestreamexperiments.FeatureStreamWithFSSExperiment
    • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.featurestreamexperiments.FeatureStreamWithFSSWithoutUpdatingExperiment
    • es.upm.fi.cig.multictbnc.experiments.implementationsexperiments.featurestreamexperiments.FeatureStreamWithoutFSSExperiment
  • es.upm.fi.cig.multictbnc.data.reader.FeatureStreamMultipleCSVReader
  • java.util.concurrent.FutureTask<V> (implements java.util.concurrent.RunnableFuture<V>)
    • javafx.concurrent.Task<V> (implements javafx.event.EventTarget, javafx.concurrent.Worker<V>)
      • es.upm.fi.cig.multictbnc.tasks.ClassificationTask
      • es.upm.fi.cig.multictbnc.tasks.EvaluationTask
      • es.upm.fi.cig.multictbnc.tasks.TrainingTask
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.HillClimbing (implements es.upm.fi.cig.multictbnc.learning.structure.StructureLearningAlgorithm)
    • es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.FirstChoiceHillClimbing
    • es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.RandomRestartHillClimbing
  • es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.HillClimbingSolution
  • es.upm.fi.cig.multictbnc.sampling.MainDataStreamSampling
  • es.upm.fi.cig.multictbnc.experiments.MainExperiment
  • es.upm.fi.cig.multictbnc.sampling.MainFeatureStreamSampling
  • es.upm.fi.cig.multictbnc.sampling.MainSampling
  • es.upm.fi.cig.multictbnc.performance.Metrics
  • es.upm.fi.cig.multictbnc.writers.performance.MetricsWriter
    • es.upm.fi.cig.multictbnc.writers.performance.ConsoleExperimentsWriter
    • es.upm.fi.cig.multictbnc.writers.performance.ExcelExperimentsWriter
  • es.upm.fi.cig.multictbnc.data.writer.MultipleCSVWriter
  • es.upm.fi.cig.multictbnc.nodes.NodeFactory<NodeType>
  • es.upm.fi.cig.multictbnc.nodes.NodeIndexer<NodeType>
  • es.upm.fi.cig.multictbnc.conceptdriftdetection.PageHinkleyTest
  • es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.PC (implements es.upm.fi.cig.multictbnc.learning.structure.StructureLearningAlgorithm)
    • es.upm.fi.cig.multictbnc.learning.structure.constraintlearning.PC.HITONPC
    • es.upm.fi.cig.multictbnc.learning.structure.hybrid.PC.PCHybridAlgorithm
  • es.upm.fi.cig.multictbnc.classification.Prediction
  • es.upm.fi.cig.multictbnc.util.ProbabilityUtil
  • es.upm.fi.cig.multictbnc.data.representation.Sequence
  • javafx.concurrent.Service<V> (implements javafx.event.EventTarget, javafx.concurrent.Worker<V>)
    • es.upm.fi.cig.multictbnc.services.ClassificationService
    • es.upm.fi.cig.multictbnc.services.EvaluationService
    • es.upm.fi.cig.multictbnc.services.TrainingService
  • es.upm.fi.cig.multictbnc.data.representation.State
  • es.upm.fi.cig.multictbnc.fss.StatisticalBasedFeatureSelection
    • es.upm.fi.cig.multictbnc.fss.ConInd (implements es.upm.fi.cig.multictbnc.fss.OnlineFeatureSubsetSelection)
  • es.upm.fi.cig.multictbnc.learning.structure.StructureLearningAlgorithmFactory
  • es.upm.fi.cig.multictbnc.fss.SubsetSelectedFeatures
  • java.lang.Throwable (implements java.io.Serializable)
    • java.lang.Exception
      • es.upm.fi.cig.multictbnc.exceptions.ErroneousSequenceException
      • es.upm.fi.cig.multictbnc.exceptions.ErroneousValueException
      • es.upm.fi.cig.multictbnc.exceptions.NeverSeenStateException
      • es.upm.fi.cig.multictbnc.exceptions.NotImplementedException
      • es.upm.fi.cig.multictbnc.exceptions.UnreadDatasetException
      • es.upm.fi.cig.multictbnc.exceptions.VariableNotFoundException
  • es.upm.fi.cig.multictbnc.writers.classification.TxtClassificationWriter
  • es.upm.fi.cig.multictbnc.util.UserInterfaceUtil
  • es.upm.fi.cig.multictbnc.util.Util
  • es.upm.fi.cig.multictbnc.performance.ValidationMethod
    • es.upm.fi.cig.multictbnc.performance.CrossValidationBinaryRelevanceMethod
    • es.upm.fi.cig.multictbnc.performance.CrossValidationMethod
    • es.upm.fi.cig.multictbnc.performance.HoldOutMethod
    • es.upm.fi.cig.multictbnc.performance.TestDatasetBinaryRelevanceMethod
    • es.upm.fi.cig.multictbnc.performance.TestDatasetMethod
  • es.upm.fi.cig.multictbnc.performance.ValidationMethodFactory

Interface Hierarchy

• es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.bn.BNScoreFunction
• es.upm.fi.cig.multictbnc.classification.Classifier
• es.upm.fi.cig.multictbnc.conceptdriftdetection.ConceptDriftScore
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.scores.ctbn.CTBNScoreFunction
• es.upm.fi.cig.multictbnc.data.reader.DatasetReader
• es.upm.fi.cig.multictbnc.experiments.Experiment
• es.upm.fi.cig.multictbnc.learning.structure.optimisation.hillclimbing.implementation.HillClimbingImplementation
• es.upm.fi.cig.multictbnc.performance.Metric
• es.upm.fi.cig.multictbnc.nodes.Node
• es.upm.fi.cig.multictbnc.fss.OnlineFeatureSubsetSelection
• es.upm.fi.cig.multictbnc.learning.parameters.ParameterLearningAlgorithm
• es.upm.fi.cig.multictbnc.models.PGM<NodeType>
• es.upm.fi.cig.multictbnc.learning.structure.constraints.StructureConstraints
• es.upm.fi.cig.multictbnc.learning.structure.StructureLearningAlgorithm
• es.upm.fi.cig.multictbnc.learning.parameters.SufficientStatistics