Package ai.libs.mlplan.multiclass.wekamlplan

Class MLPlanWekaBuilder

  • All Implemented Interfaces:
    ai.libs.mlplan.core.IMLPlanBuilder<ai.libs.jaicore.ml.weka.classification.learner.IWekaClassifier,​MLPlanWekaBuilder>, org.api4.java.common.control.ILoggingCustomizable
    public class MLPlanWekaBuilder
extends ai.libs.mlplan.core.AbstractMLPlanBuilder<ai.libs.jaicore.ml.weka.classification.learner.IWekaClassifier,​MLPlanWekaBuilder>

    • Field Summary

      • Fields inherited from class ai.libs.mlplan.core.AbstractMLPlanBuilder

        DEFAULT_PERFORMANCE_MEASURE, DEFAULT_SEARCH_NUM_MC_ITERATIONS, DEFAULT_SEARCH_TRAIN_FOLD_SIZE, DEFAULT_SELECTION_NUM_MC_ITERATIONS, DEFAULT_SELECTION_TRAIN_FOLD_SIZE, factoryForPipelineEvaluationInSearchPhase, factoryForPipelineEvaluationInSelectionPhase

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      MLPlan4Weka build()  
      MLPlanWekaBuilder getSelf()  
      MLPlanWekaBuilder withDataset​(org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?> dataset)  
      void withLearningCurveExtrapolationEvaluation​(int[] anchorpoints, ai.libs.jaicore.ml.core.filter.sampling.inmemory.factories.interfaces.ISamplingAlgorithmFactory<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,​? extends ai.libs.jaicore.ml.core.filter.sampling.inmemory.ASamplingAlgorithm<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>>> subsamplingAlgorithmFactory, double trainSplitForAnchorpointsMeasurement, ai.libs.jaicore.ml.functionprediction.learner.learningcurveextrapolation.LearningCurveExtrapolationMethod extrapolationMethod)
      Allows to use learning curve extrapolation for predicting the quality of candidate solutions.
      MLPlanWekaBuilder withPreferredComponentsFile​(java.io.File preferredComponentsFile, java.lang.String preferableCompnentMethodPrefix)
      Creates a preferred node evaluator that can be used to prefer components over other components.
      MLPlanWekaBuilder withTinyWekaSearchSpace()
      Sets the search space to a tiny weka search space configuration.

      • Methods inherited from class ai.libs.mlplan.core.AbstractMLPlanBuilder

        build, checkPreconditionsForInitialization, getAlgorithmConfig, getCandidateEvaluationTimeOut, getComponentParameterConfigurations, getComponents, getDataset, getHASCOFactory, getLearnerEvaluationFactoryForSearchPhase, getLearnerEvaluationFactoryForSelectionPhase, getLearnerFactory, getLoggerName, getNodeEvaluationTimeOut, getPortionOfDataReservedForSelectionPhase, getRequestedInterface, getSearchEvaluatorFactory, getSearchSelectionDatasetSplitter, getSearchSpaceConfigFile, getSelectionEvaluatorFactory, getTimeOut, prepareNodeEvaluatorInFactoryWithData, setLoggerName, withAlgorithmConfig, withAlgorithmConfigFile, withCandidateEvaluationTimeOut, withClassifierFactory, withDatasetSplitterForSearchSelectionSplit, withMCCVBasedCandidateEvaluationInSearchPhase, withMCCVBasedCandidateEvaluationInSelectionPhase, withNodeEvaluationTimeOut, withNumCpus, withPipelineValidityCheckingNodeEvaluator, withPortionOfDataReservedForSelection, withPreferredNodeEvaluator, withRandomCompletionBasedBestFirstSearch, withRequestedInterface, withSearchFactory, withSearchPhaseEvaluatorFactory, withSearchSpaceConfigFile, withSeed, withSelectionPhaseEvaluatorFactory, withTimeOut

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Constructor Detail

      • MLPlanWekaBuilder

        public MLPlanWekaBuilder()
                  throws java.io.IOException
        Throws:
        java.io.IOException

    • Method Detail

      • withTinyWekaSearchSpace

        public MLPlanWekaBuilder withTinyWekaSearchSpace()
                                          throws java.io.IOException
        Sets the search space to a tiny weka search space configuration.
        Throws:
        java.io.IOException - Thrown if the resource file cannot be read.

      • withLearningCurveExtrapolationEvaluation

        public void withLearningCurveExtrapolationEvaluation​(int[] anchorpoints,
                                                     ai.libs.jaicore.ml.core.filter.sampling.inmemory.factories.interfaces.ISamplingAlgorithmFactory<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,​? extends ai.libs.jaicore.ml.core.filter.sampling.inmemory.ASamplingAlgorithm<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>>> subsamplingAlgorithmFactory,
                                                     double trainSplitForAnchorpointsMeasurement,
                                                     ai.libs.jaicore.ml.functionprediction.learner.learningcurveextrapolation.LearningCurveExtrapolationMethod extrapolationMethod)
        Allows to use learning curve extrapolation for predicting the quality of candidate solutions.
        Parameters:
        anchorpoints - The anchor points for which samples are actually evaluated on the respective data.
        subsamplingAlgorithmFactory - The factory for the sampling algorithm that is to be used to randomly draw training instances.
        trainSplitForAnchorpointsMeasurement - The training fold size for measuring the acnhorpoints.
        extrapolationMethod - The method to be used in order to extrapolate the learning curve from the anchorpoints.

      • withPreferredComponentsFile

        public MLPlanWekaBuilder withPreferredComponentsFile​(java.io.File preferredComponentsFile,
                                                     java.lang.String preferableCompnentMethodPrefix)
                                              throws java.io.IOException
        Creates a preferred node evaluator that can be used to prefer components over other components.
        Parameters:
        preferredComponentsFile - The file containing a priority list of component names.
        preferableCompnentMethodPrefix - The prefix of a method's name for refining a complex task to preferable components.
        Returns:
        The builder object.
        Throws:
        java.io.IOException - Thrown if a problem occurs while trying to read the file containing the priority list.

      • withDataset

        public MLPlanWekaBuilder withDataset​(org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?> dataset)
        Overrides:
        withDataset in class ai.libs.mlplan.core.AbstractMLPlanBuilder<ai.libs.jaicore.ml.weka.classification.learner.IWekaClassifier,​MLPlanWekaBuilder>

      • build

        public MLPlan4Weka build()
        Overrides:
        build in class ai.libs.mlplan.core.AbstractMLPlanBuilder<ai.libs.jaicore.ml.weka.classification.learner.IWekaClassifier,​MLPlanWekaBuilder>