smile.regression

Class RegressionTree.Trainer

java.lang.Object

smile.regression.RegressionTrainer<double[]>

smile.regression.RegressionTree.Trainer

Enclosing class:

RegressionTree

public static class RegressionTree.Trainer
extends RegressionTrainer<double[]>

Trainer for regression tree.

Constructor Summary

Constructors

Constructor and Description
Trainer(Attribute[] attributes, int J) Constructor.
Trainer(int J) Constructor.
Trainer(int numFeatures, int J) Constructor.

Method Summary

Modifier and Type	Method and Description
RegressionTree.Trainer	setMaximumLeafNodes(int J) Sets the maximum number of leaf nodes in the tree.
RegressionTree	train(double[][] x, double[] y) Learns a regression model with given training data.
RegressionTree	train(int[][] x, double[] y)

Methods inherited from class smile.regression.RegressionTrainer

setAttributes

Methods inherited from class java.lang.Object

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

Constructor Detail

Trainer

public Trainer(int J)

Constructor.

Parameters:

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

Trainer

public Trainer(Attribute[] attributes,
               int J)

Constructor.

Parameters:

attributes - the attributes of independent variable.

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

Trainer

public Trainer(int numFeatures,
               int J)

Constructor.

Parameters:

numFeatures - the number of features.

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

Method Detail

setMaximumLeafNodes

public RegressionTree.Trainer setMaximumLeafNodes(int J)

Sets the maximum number of leaf nodes in the tree.

Parameters:

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

train

public RegressionTree train(double[][] x,
                            double[] y)

Description copied from class: RegressionTrainer

Learns a regression model with given training data.

Specified by:

train in class RegressionTrainer<double[]>

Parameters:

x - the training instances.

y - the training response values.

Returns:

a trained regression model.

train

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