Package ai.libs.jaicore.ml.tsc.classifier.trees

Interface TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig

  • All Superinterfaces:
    org.aeonbits.owner.Config, ai.libs.jaicore.basic.algorithm.IAlgorithmConfig, ai.libs.jaicore.basic.IConfig, ai.libs.jaicore.basic.algorithm.IRandomAlgorithmConfig, org.aeonbits.owner.Mutable, java.io.Serializable
    Enclosing class:
    TimeSeriesForestLearningAlgorithm
    public static interface TimeSeriesForestLearningAlgorithm.ITimeSeriesForestConfig
extends ai.libs.jaicore.basic.algorithm.IRandomAlgorithmConfig

    • Nested Class Summary

      • Nested classes/interfaces inherited from interface org.aeonbits.owner.Config

        org.aeonbits.owner.Config.ConverterClass, org.aeonbits.owner.Config.DecryptorClass, org.aeonbits.owner.Config.DefaultValue, org.aeonbits.owner.Config.DisableableFeature, org.aeonbits.owner.Config.DisableFeature, org.aeonbits.owner.Config.EncryptedValue, org.aeonbits.owner.Config.HotReload, org.aeonbits.owner.Config.HotReloadType, org.aeonbits.owner.Config.Key, org.aeonbits.owner.Config.LoadPolicy, org.aeonbits.owner.Config.LoadType, org.aeonbits.owner.Config.PreprocessorClasses, org.aeonbits.owner.Config.Separator, org.aeonbits.owner.Config.Sources, org.aeonbits.owner.Config.TokenizerClass

    • Field Summary

      Fields 
      Modifier and Type Field Description
      static java.lang.String K_FEATURECACHING  
      static java.lang.String K_MAXDEPTH  
      static java.lang.String K_NUMTREES  

      • Fields inherited from interface ai.libs.jaicore.basic.algorithm.IAlgorithmConfig

        K_CPUS, K_MEMORY, K_THREADS, K_TIMEOUT

      • Fields inherited from interface ai.libs.jaicore.basic.algorithm.IRandomAlgorithmConfig

        K_SEED

    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method Description
      int maxDepth()
      Maximum depth of the trained trees.
      int numTrees()
      Number of trees to be trained.
      boolean useFeatureCaching()
      Indicator whether feature caching should be used.

      • Methods inherited from interface ai.libs.jaicore.basic.algorithm.IAlgorithmConfig

        cpus, memory, threads, timeout

      • Methods inherited from interface ai.libs.jaicore.basic.IConfig

        loadPropertiesFromFile, loadPropertiesFromList, loadPropertiesFromResource

      • Methods inherited from interface ai.libs.jaicore.basic.algorithm.IRandomAlgorithmConfig

        seed

      • Methods inherited from interface org.aeonbits.owner.Mutable

        addPropertyChangeListener, addPropertyChangeListener, clear, load, load, removeProperty, removePropertyChangeListener, setProperty

    • Method Detail

      • numTrees

        @Key("numtrees")
@DefaultValue("-1")
int numTrees()
        Number of trees to be trained.

      • maxDepth

        @Key("maxdepth")
@DefaultValue("-1")
int maxDepth()
        Maximum depth of the trained trees.

      • useFeatureCaching

        @Key("featurecaching")
@DefaultValue("false")
boolean useFeatureCaching()
        Indicator whether feature caching should be used. Usage for datasets with many attributes is not recommended due to a high number of possible intervals.