/**
* Generates the classifier.
*
* @param instances the data to train with
* @throws Exception if classifier can't be built successfully
*/
@Override
public void buildClassifier(Instances instances) throws Exception {
// can classifier handle the data?
getCapabilities().testWithFail(instances);
// remove instances with missing class
instances = new Instances(instances);
instances.deleteWithMissingClass();
ModelSelection modSelection;
if (m_binarySplits) {
modSelection =
new BinC45ModelSelection(
m_minNumObj, instances, m_useMDLcorrection, m_doNotMakeSplitPointActualValue);
} else {
modSelection =
new C45ModelSelection(
m_minNumObj, instances, m_useMDLcorrection, m_doNotMakeSplitPointActualValue);
}
if (m_unpruned) {
m_root = new MakeDecList(modSelection, m_minNumObj);
} else if (m_reducedErrorPruning) {
m_root = new MakeDecList(modSelection, m_numFolds, m_minNumObj, m_Seed);
} else {
m_root = new MakeDecList(modSelection, m_CF, m_minNumObj);
}
m_root.buildClassifier(instances);
if (m_binarySplits) {
((BinC45ModelSelection) modSelection).cleanup();
} else {
((C45ModelSelection) modSelection).cleanup();
}
}
/**
* Generates the classifier.
*
* @param instances the data to train the classifier with
* @throws Exception if classifier can't be built successfully
*/
public void buildClassifier(Instances instances) throws Exception {
ModelSelection modSelection;
if (m_binarySplits)
modSelection = new BinC45ModelSelection(m_minNumObj, instances, m_useMDLcorrection);
else modSelection = new C45ModelSelection(m_minNumObj, instances, m_useMDLcorrection);
if (!m_reducedErrorPruning)
m_root =
new C45PruneableClassifierTree(
modSelection, !m_unpruned, m_CF, m_subtreeRaising, !m_noCleanup, m_collapseTree);
else
m_root =
new PruneableClassifierTree(modSelection, !m_unpruned, m_numFolds, !m_noCleanup, m_Seed);
m_root.buildClassifier(instances);
if (m_binarySplits) {
((BinC45ModelSelection) modSelection).cleanup();
} else {
((C45ModelSelection) modSelection).cleanup();
}
}