Package ai.libs.mlplan.multilabel.mekamlplan

Class ML2PlanMekaBuilder

  • All Implemented Interfaces:
    ai.libs.mlplan.core.IMLPlanBuilder<ai.libs.jaicore.ml.classification.multilabel.learner.IMekaClassifier,​ML2PlanMekaBuilder>, org.api4.java.common.control.ILoggingCustomizable
    public class ML2PlanMekaBuilder
extends ai.libs.mlplan.core.AMLPlanBuilder<ai.libs.jaicore.ml.classification.multilabel.learner.IMekaClassifier,​ML2PlanMekaBuilder>

    • Constructor Summary

      Constructors 
      Constructor Description
      ML2PlanMekaBuilder()  
      ML2PlanMekaBuilder​(ai.libs.mlplan.core.IProblemType<ai.libs.jaicore.ml.classification.multilabel.learner.IMekaClassifier> problemType)  

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      ML2PlanMekaBuilder getSelf()  
      ML2PlanMekaBuilder withAutoMEKADefaultConfiguration()
      Configures ML-Plan with the configuration as compared to AutoMEKA_GGP and GA-Auto-MLC.
      ML2PlanMekaBuilder withPerformanceMeasure​(org.api4.java.ai.ml.classification.multilabel.evaluation.loss.IMultiLabelClassificationPredictionPerformanceMeasure measure)
      Sets the performance measure to evaluate a candidate solution's generalization performance.

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

        build, build, checkPreconditionsForInitialization, getAlgorithmConfig, getCandidateEvaluationTimeOut, getComponentParameterConfigurations, getComponents, getDataset, getHASCOFactory, getLearnerEvaluationFactoryForSearchPhase, getLearnerEvaluationFactoryForSelectionPhase, getLearnerFactory, getLoggerName, getMetricForSearchPhase, getMetricForSelectionPhase, getNodeEvaluationTimeOut, getPipelineValidityCheckingNodeEvaluator, getPortionOfDataReservedForSelectionPhase, getPreferredComponents, getPreferredNodeEvaluators, getRequestedInterface, getSafeGuardFactory, getSearchEvaluatorFactory, getSearchSelectionDatasetSplitter, getSearchSpaceConfigFile, getSelectionEvaluatorFactory, getTimeOut, getTimeoutPrecautionOffsetInSeconds, setLoggerName, withAlgorithmConfig, withAlgorithmConfigFile, withCandidateEvaluationTimeOut, withDataset, withDatasetSplitterForSearchSelectionSplit, withLearnerFactory, withMCCVBasedCandidateEvaluationInSearchPhase, withMCCVBasedCandidateEvaluationInSelectionPhase, withNodeEvaluationTimeOut, withNumCpus, withPerformanceMeasure, withPerformanceMeasureForSearchPhase, withPerformanceMeasureForSelectionPhase, withPipelineValidityCheckingNodeEvaluator, withPortionOfDataReservedForSelection, withPreferredComponents, withPreferredComponentsFile, withPreferredNodeEvaluator, withProblemType, withRequestedInterface, withSafeGuardFactory, withSearchFactory, withSearchPhaseEvaluatorFactory, withSearchSpaceConfigFile, withSeed, withSelectionPhaseEvaluatorFactory, withTimeOut, withTimeoutPrecautionOffsetInSeconds

      • Methods inherited from class java.lang.Object

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

    • Constructor Detail

      • ML2PlanMekaBuilder

        public ML2PlanMekaBuilder()
                   throws java.io.IOException
        Throws:
        java.io.IOException

      • ML2PlanMekaBuilder

        public ML2PlanMekaBuilder​(ai.libs.mlplan.core.IProblemType<ai.libs.jaicore.ml.classification.multilabel.learner.IMekaClassifier> problemType)
                   throws java.io.IOException
        Throws:
        java.io.IOException

    • Method Detail

      • withAutoMEKADefaultConfiguration

        public ML2PlanMekaBuilder withAutoMEKADefaultConfiguration()
        Configures ML-Plan with the configuration as compared to AutoMEKA_GGP and GA-Auto-MLC.
        Returns:
        The builder object.

      • withPerformanceMeasure

        public ML2PlanMekaBuilder withPerformanceMeasure​(org.api4.java.ai.ml.classification.multilabel.evaluation.loss.IMultiLabelClassificationPredictionPerformanceMeasure measure)
        Sets the performance measure to evaluate a candidate solution's generalization performance. Caution: This resets the evaluators to MCCV for both search and selection phase if these are not already MCCVs.
        Parameters:
        lossFunction - The loss function to be used.
        Returns:
        The builder object.