public class JointRegressorTrainingNode extends AbstractTrainingNode<Regressor>
DEFAULT_SIZE, depth, greaterThan, lessThanOrEqual, numExamples, split, splitID, splitValue
Constructor and Description |
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JointRegressorTrainingNode(RegressorImpurity impurity,
Dataset<Regressor> examples,
boolean normalize)
Constructor which creates the inverted file.
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Modifier and Type | Method and Description |
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List<AbstractTrainingNode<Regressor>> |
buildTree(int[] featureIDs)
Builds a tree according to CART (as it does not do multi-way splits on categorical values like C4.5).
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Node<Regressor> |
convertTree()
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double |
getImpurity()
The impurity score of this node.
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copy, getDepth, getNextNode, getNumExamples, isLeaf
public JointRegressorTrainingNode(RegressorImpurity impurity, Dataset<Regressor> examples, boolean normalize)
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.public double getImpurity()
Node
public List<AbstractTrainingNode<Regressor>> buildTree(int[] featureIDs)
buildTree
in class AbstractTrainingNode<Regressor>
featureIDs
- Indices of the features available in this split.public Node<Regressor> convertTree()
convertTree
in class AbstractTrainingNode<Regressor>
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