public static class DecisionTree.Trainer extends ClassifierTrainer<double[]>
Constructor and Description |
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DecisionTree.Trainer(Attribute[] attributes,
int J)
Constructor.
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DecisionTree.Trainer(int J)
Constructor.
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Modifier and Type | Method and Description |
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void |
setMaximumLeafNodes(int J)
Sets the maximum number of leaf nodes in the tree.
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void |
setSplitRule(DecisionTree.SplitRule rule)
Sets the splitting rule.
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DecisionTree |
train(double[][] x,
int[] y)
Learns a classifier with given training data.
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setAttributes
public DecisionTree.Trainer(int J)
J
- the maximum number of leaf nodes in the tree.public DecisionTree.Trainer(Attribute[] attributes, int J)
attributes
- the attributes of independent variable.J
- the maximum number of leaf nodes in the tree.public void setSplitRule(DecisionTree.SplitRule rule)
rule
- the splitting rule.public void setMaximumLeafNodes(int J)
J
- the maximum number of leaf nodes in the tree.public DecisionTree train(double[][] x, int[] y)
ClassifierTrainer
train
in class ClassifierTrainer<double[]>
x
- the training instances.y
- the training labels.Copyright © 2015. All rights reserved.