Package com.imsl.test.example.datamining.decisionTree

Class RandomTreesEx1

java.lang.Object

com.imsl.test.example.datamining.decisionTree.RandomTreesEx1

public class RandomTreesEx1
extends Object

Fits a random forest to the Kyphosis data using ALACART decision trees and generates predictions on a test set.

This example builds a random forest RandomTrees with ALACART decision trees. A single tree and the random forest are fit to the Kyphosis data and predictions for a test-data set consisting of 10 "new" cases are generated.

The Kyphosis data 81 cases represent 81 children who have undergone surgery to correct a type of spinal deformity known as Kyphosis. The response variable is the presence or absence of Kyphosis after the surgery. The three predictors are:

• Age of the patient in months
• Start, the number of the vertebra where the surgery started
• Number, the number of vertebra involved in the surgery

See Also:

• Code
• Output

Constructor Summary

Constructors

Constructor	Description
RandomTreesEx1()

Method Summary

Modifier and Type	Method	Description
static void	main(String[] args)

Methods inherited from class java.lang.Object

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

Constructor Details

RandomTreesEx1

public RandomTreesEx1()

Method Details

main

public static void main(String[] args)
                 throws Exception

Throws:

Exception