com.imsl.test.example.datamining.decisionTree

Class DecisionTreeEx1

java.lang.Object

com.imsl.test.example.datamining.decisionTree.DecisionTreeEx1

public class DecisionTreeEx1
extends Object

Fits a decision tree to the golf data using C45 and ALACART.

In this example, we use a small data set with response variable, Play, which indicates whether a golfer plays (1) or does not play (0) golf under weather conditions measured by Temperature, Humidity, Outlook (Sunny (0), Overcast (1), Rainy (2)), and Wind (True (0), False (1)). A decision tree is generated by C45 and the ALACART class. The control parameters are adjusted because of the small data size and no cross-validation or pruning is performed. The maximal trees are printed out using the method, DecisionTree.printDecisionTree Notice that C45 splits on Outlook, then Humidity and Wind, while ALACART splits on Outlook, then Temperature.

See Also:

Code, Output

Constructor Summary

Constructors

Constructor and Description
DecisionTreeEx1()

Method Summary

Modifier and Type	Method and 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 Detail

DecisionTreeEx1

public DecisionTreeEx1()

Method Detail

main

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

Throws:

Exception