Package unifeat.featureSelection.embedded.TreeBasedMethods

Class TreeBasedMethods

java.lang.Object
unifeat.featureSelection.FeatureSelection
unifeat.featureSelection.embedded.EmbeddedApproach
unifeat.featureSelection.embedded.TreeBasedMethods.TreeBasedMethods
Direct Known Subclasses:
DecisionTreeBasedMethod, RandomForestMethod
public abstract class TreeBasedMethods extends EmbeddedApproach
The abstract class contains the main methods and fields that are used in all Tree-based feature selection methods. This class inherits from EmbeddedApproach class.
Author:
Sina Tabakhi
See Also:

  • Field Details

    • TEMP_PATH

      protected final String TEMP_PATH

    • TREE_TYPE

      protected final TreeType TREE_TYPE

  • Constructor Details

    • TreeBasedMethods

      public TreeBasedMethods(Object... arguments)
      Initializes the parameters
      Parameters:
      arguments - array of parameter contains (path, tree type) in which path is the path of the project, and tree type is the type of tree

  • Method Details

    • selectedFeatureSubset

      protected abstract void selectedFeatureSubset(String tree)
      Finds the feature subset from the nodes of the created tree
      Parameters:
      tree - the generated tree based on the train set

    • buildClassifier

      protected abstract String buildClassifier(weka.core.Instances dataTrain)
      Generates a classifier using input data
      Parameters:
      dataTrain - the data to train the classifier
      Returns:
      the output of the generated classifier