Class JointRegressorTrainingNode

All Implemented Interfaces:
Serializable, Node<Regressor>

public class JointRegressorTrainingNode extends AbstractTrainingNode<Regressor>
A decision tree node used at training time. Contains a list of the example indices currently found in this node, the current impurity and a bunch of other statistics.
See Also:
  • Constructor Details

    • JointRegressorTrainingNode

      public JointRegressorTrainingNode(RegressorImpurity impurity, Dataset<Regressor> examples, boolean normalize, AbstractTrainingNode.LeafDeterminer leafDeterminer)
      Constructor which creates the inverted file.
      impurity - The impurity function to use.
      examples - The training data.
      normalize - Normalizes the leaves so each leaf has a distribution which sums to 1.0.
      leafDeterminer - Contains parameters needed to determine whether a node is a leaf.
  • Method Details

    • getImpurity

      public double getImpurity()
      Description copied from interface: Node
      The impurity score of this node.
      The node impurity.
    • getWeightSum

      public float getWeightSum()
      Description copied from class: AbstractTrainingNode
      The sum of the weights associated with this node's examples.
      Specified by:
      getWeightSum in class AbstractTrainingNode<Regressor>
      the sum of the weights associated with this node's examples.
    • buildTree

      public List<AbstractTrainingNode<Regressor>> buildTree(int[] featureIDs, SplittableRandom rng, boolean useRandomSplitPoints)
      Builds a tree according to CART (as it does not do multi-way splits on categorical values like C4.5).
      Specified by:
      buildTree in class AbstractTrainingNode<Regressor>
      featureIDs - Indices of the features available in this split.
      rng - Splittable random number generator.
      useRandomSplitPoints - Whether to choose split points for features at random.
      A possibly empty list of TrainingNodes.
    • convertTree

      public Node<Regressor> convertTree()
      Generates a test time tree (made of SplitNode and LeafNode) from the tree rooted at this node.
      Specified by:
      convertTree in class AbstractTrainingNode<Regressor>
      A subtree using the SplitNode and LeafNode classes.