474 CHAPTER 15 | WRITING NEW LEARNING SCHEMES
/**
* Builds Id3 decision tree classifier.
*
* @param data the training data
* @exception Exception if classifier can't be built successfully
*/
public void buildClassifier(Instances data) throws Exception {if (!data.classAttribute().isNominal()) {
throw new UnsupportedClassTypeException("Id3: nominal class, please.");
}
Enumeration enumAtt = data.enumerateAttributes();
while (enumAtt.hasMoreElements()) {
if (!((Attribute) enumAtt.nextElement()).isNominal()) {
throw new UnsupportedAttributeTypeException("Id3: only nominal " +
"attributes, please.");
}
}
Enumeration enum = data.enumerateInstances();
while (enum.hasMoreElements()) {
if (((Instance) enum.nextElement()).hasMissingValue()) {
throw new NoSupportForMissingValuesException("Id3: no missing values, "
+ "please.");}
}
data = new Instances(data);
data.deleteWithMissingClass();
makeTree(data);
}/**
* Method for building an Id3 tree.
*
* @param data the training data
* @exception Exception if decision tree can't be built successfully
*/
private void makeTree(Instances data) throws Exception {// Check if no instances have reached this node.
if (data.numInstances() == 0) {
m_Attribute = null;Figure 15.1(continued)