smile.classification

Class DecisionTree.Trainer

java.lang.Object

smile.classification.ClassifierTrainer<double[]>

smile.classification.DecisionTree.Trainer

Enclosing class:

DecisionTree

public static class DecisionTree.Trainer
extends ClassifierTrainer<double[]>

Trainer for decision tree classifiers.

Constructor Summary

Constructors

Constructor and Description
Trainer() Default constructor of maximal 100 leaf nodes in the tree.
Trainer(smile.data.Attribute[] attributes, int maxNodes) Constructor.
Trainer(int maxNodes) Constructor.

Method Summary

Modifier and Type	Method and Description
DecisionTree.Trainer	setMaxNodes(int maxNodes) Sets the maximum number of leaf nodes in the tree.
DecisionTree.Trainer	setNodeSize(int nodeSize) Sets the minimum size of leaf nodes.
DecisionTree.Trainer	setSplitRule(DecisionTree.SplitRule rule) Sets the splitting rule.
DecisionTree	train(double[][] x, int[] y) Learns a classifier with given training data.

Methods inherited from class smile.classification.ClassifierTrainer

setAttributes

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Trainer

public Trainer()

Default constructor of maximal 100 leaf nodes in the tree.

Trainer

public Trainer(int maxNodes)

Constructor.

Parameters:

maxNodes - the maximum number of leaf nodes in the tree.

Trainer

public Trainer(smile.data.Attribute[] attributes,
               int maxNodes)

Constructor.

Parameters:

attributes - the attributes of independent variable.

maxNodes - the maximum number of leaf nodes in the tree.

Method Detail

setSplitRule

public DecisionTree.Trainer setSplitRule(DecisionTree.SplitRule rule)

Sets the splitting rule.

Parameters:

rule - the splitting rule.

setMaxNodes

public DecisionTree.Trainer setMaxNodes(int maxNodes)

Sets the maximum number of leaf nodes in the tree.

Parameters:

maxNodes - the maximum number of leaf nodes in the tree.

setNodeSize

public DecisionTree.Trainer setNodeSize(int nodeSize)

Sets the minimum size of leaf nodes.

Parameters:

nodeSize - the minimum size of leaf nodes..

train

public DecisionTree train(double[][] x,
                          int[] y)

Description copied from class: ClassifierTrainer

Learns a classifier with given training data.

Specified by:

train in class ClassifierTrainer<double[]>

Parameters:

x - the training instances.

y - the training labels.

Returns:

a trained classifier.