/// <summary> Generates the classifier.
///
/// </summary>
/// <exception cref="Exception">if classifier can't be built successfully
/// </exception>
public override void buildClassifier(Instances instances)
{
ModelSelection modSelection;
if (m_binarySplits)
modSelection = new BinC45ModelSelection(m_minNumObj, instances);
else
modSelection = new C45ModelSelection(m_minNumObj, instances);
if (!m_reducedErrorPruning)
m_root = new C45PruneableClassifierTree(modSelection, !m_unpruned, m_CF, m_subtreeRaising, !m_noCleanup);
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();
}
}
/// <summary> Returns a newly created tree.
///
/// </summary>
/// <param name="data">the training data
/// </param>
/// <exception cref="Exception">if something goes wrong
/// </exception>
protected internal virtual ClassifierTree getNewTree(Instances data)
{
ClassifierTree newTree = new ClassifierTree(m_toSelectModel);
newTree.buildTree(data, false);
return newTree;
}
/// <summary> Returns a newly created tree.
///
/// </summary>
/// <param name="data">the training data
/// </param>
/// <param name="test">the pruning data.
/// </param>
/// <exception cref="Exception">if something goes wrong
/// </exception>
protected internal virtual ClassifierTree getNewTree(Instances train, Instances test)
{
ClassifierTree newTree = new ClassifierTree(m_toSelectModel);
newTree.buildTree(train, test, false);
return newTree;
}
public override void buildClassifier(string fileName, Instances instances)
{
XmlDocument dom = new XmlDocument();
dom.Load(fileName);
XmlNode xNode = dom.DocumentElement;
if ((xNode.Name == Constants.DECISION_TREE_ELEMENT) && (xNode.HasChildNodes))
{
foreach (XmlAttribute xAttribute in xNode.Attributes)
{
if (xAttribute.Name == Constants.PRUNED_ATTRIBUTE)
{
if (xAttribute.Value == "True")
this.m_unpruned = true;
else
this.m_unpruned = false;
}
else if (xAttribute.Name == Constants.CONFIDENCE_ATTRIBUTE)
this.m_CF = (float) Convert.ToDouble(xAttribute.Value);
else if (xAttribute.Name == Constants.MIN_NUM_OBJECTS_ATTRIBUTE)
this.m_minNumObj = Convert.ToInt32(xAttribute.Value);
else if (xAttribute.Name == Constants.USE_LAPLACE_ATTRIBUTE)
{
if (xAttribute.Value == "True")
this.m_useLaplace = true;
else
this.m_useLaplace = false;
}
else if (xAttribute.Name == Constants.REDUCED_ERROR_PRUNING_ATTRIBUTE)
{
if (xAttribute.Value == "True")
this.m_reducedErrorPruning = true;
else
this.m_reducedErrorPruning = false;
}
else if (xAttribute.Name == Constants.NUM_FOLDS_ATTRIBUTE)
this.m_numFolds = Convert.ToInt32(xAttribute.Value);
else if (xAttribute.Name == Constants.BINARY_SPLITS_ATTRIBUTE)
{
if (xAttribute.Value == "True")
this.m_binarySplits = true;
else
this.m_binarySplits = false;
}
else if (xAttribute.Name == Constants.SUBTREE_RAISING_ATTRIBUTE)
{
if (xAttribute.Value == "True")
this.m_subtreeRaising = true;
else
this.m_subtreeRaising = false;
}
else if (xAttribute.Name == Constants.NO_CLEANUP_ATTRIBUTE)
{
if (xAttribute.Value == "True")
this.m_noCleanup = true;
else
this.m_noCleanup = false;
}
else if (xAttribute.Name == Constants.SEED_ATTRIBUTE)
this.m_Seed = Convert.ToInt32(xAttribute.Value);
}
//Going through the subtrees
foreach (XmlNode iNode in xNode.ChildNodes)
{
if (iNode.Name == Constants.C45_PRUNEABLE_ELEMENT)
{
this.m_root = new C45PruneableClassifierTree(iNode, instances);
}
}
}
}
