/// <summary>
/// Attaches a new leaf node to the supplied node, along
/// the specified arc.
/// </summary>
public DecisionTreeNode addLeafNode(DecisionTreeNode parent,
int arcNum,
String label,
AttributeMask mask,
int numTrainingExamplesReachHere,
int bestTrainingTargetIndex,
int numTrainingEgsCorrectClassUsingBestTrainingIndex,
int numTestingEgsCorrectClassUsingBestTrainingIndex,
int numTestingExamplesReachHere,
int bestTestingTargetIndex,
int numTestingEgsCorrectClassUsingBestTestingIndex,
int numTrainingEgsCorrectClassUsingBestTestingIndex)
{
// Create new leaf node.
DecisionTreeNode leaf =
new DecisionTreeNode(parent, label, null, mask);
// Set the node statistics.
leaf.setTrainingStats(numTrainingExamplesReachHere,
bestTrainingTargetIndex,
numTrainingEgsCorrectClassUsingBestTrainingIndex,
numTestingEgsCorrectClassUsingBestTrainingIndex);
leaf.setTestingStats(numTestingExamplesReachHere,
bestTestingTargetIndex,
numTestingEgsCorrectClassUsingBestTestingIndex,
numTrainingEgsCorrectClassUsingBestTestingIndex);
// Update the tree statistics.
TrainingCorrect += numTrainingEgsCorrectClassUsingBestTrainingIndex;
TestingCorrect += numTestingEgsCorrectClassUsingBestTrainingIndex;
// Now, attach the new leaf to the supplied node.
if (parent != null)
{
parent.setChild(arcNum, leaf);
}
// Add a reference to the new node to the node list.
Nodes.Add(leaf);
// Determine if the tree is complete.
if (findIncompleteNode((DecisionTreeNode)Nodes[0], new int[1]) == null)
{
Complete = true;
}
return(leaf);
}
/// <summary>
/// Attaches a new internal node to the supplied node,
/// along the specified arc.
/// </summary>
/// <param name="parent">The node in the current tree to attach
/// the internal node to. If the node is null, the
/// new internal node becomes the root of the tree.</param>
/// <param name="arcNum">The arc number (or attribute value
/// index) along which to attach the new node.</param>
/// <param name="attributePosition">The position of the
/// attribute used to split at the new node, relative
/// to the other attributes in the dataset.</param>
/// <param name="att">The attribute used to split at the new
/// node.</param>
/// <returns>A reference to the new internal node.</returns>
public DecisionTreeNode addInternalNode(DecisionTreeNode parent,
int arcNum,
int attributePosition,
Attribute att,
AttributeMask mask,
int numTrainingExamplesReachHere,
int bestTrainingTargetIndex,
int numTrainingEgsCorrectClassUsingBestTrainingIndex,
int numTestingEgsCorrectClassUsingBestTrainingIndex,
int numTestingExamplesReachHere,
int bestTestingTargetIndex,
int numTestingEgsCorrectClassUsingBestTestingIndex,
int numTrainingEgsCorrectClassUsingBestTestingIndex)
{
// Create a new internal node.
DecisionTreeNode internalNode = new DecisionTreeNode(parent, att.getName(), att.getValueNames(), mask);
// Set the node statistics.
internalNode.setTrainingStats(numTrainingExamplesReachHere,
bestTrainingTargetIndex,
numTrainingEgsCorrectClassUsingBestTrainingIndex,
numTestingEgsCorrectClassUsingBestTrainingIndex);
internalNode.setTestingStats(numTestingExamplesReachHere,
bestTestingTargetIndex,
numTestingEgsCorrectClassUsingBestTestingIndex,
numTrainingEgsCorrectClassUsingBestTestingIndex);
// Update the tree statistics.
InternalNodes++;
// Now, attach the new internal node to the supplied node.
if (parent != null)
{
parent.setChild(arcNum, internalNode);
}
// Add a reference to the new node to the node list.
Nodes.Add(internalNode);
return(internalNode);
}
/// <summary>
/// Attaches a new internal node to the supplied node,
/// along the specified arc.
/// </summary>
/// <param name="parent">The node in the current tree to attach
/// the internal node to. If the node is null, the
/// new internal node becomes the root of the tree.</param>
/// <param name="arcNum">The arc number (or attribute value
/// index) along which to attach the new node.</param>
/// <param name="attributePosition">The position of the
/// attribute used to split at the new node, relative
/// to the other attributes in the dataset.</param>
/// <param name="att">The attribute used to split at the new
/// node.</param>
/// <returns>A reference to the new internal node.</returns>
public DecisionTreeNode addInternalNode(DecisionTreeNode parent,
int arcNum,
int attributePosition,
Attribute att,
AttributeMask mask,
int numTrainingExamplesReachHere,
int bestTrainingTargetIndex,
int numTrainingEgsCorrectClassUsingBestTrainingIndex,
int numTestingEgsCorrectClassUsingBestTrainingIndex,
int numTestingExamplesReachHere,
int bestTestingTargetIndex,
int numTestingEgsCorrectClassUsingBestTestingIndex,
int numTrainingEgsCorrectClassUsingBestTestingIndex)
{
// Create a new internal node.
DecisionTreeNode internalNode = new DecisionTreeNode(parent, att.getName(), att.getValueNames(), mask);
// Set the node statistics.
internalNode.setTrainingStats(numTrainingExamplesReachHere,
bestTrainingTargetIndex,
numTrainingEgsCorrectClassUsingBestTrainingIndex,
numTestingEgsCorrectClassUsingBestTrainingIndex);
internalNode.setTestingStats(numTestingExamplesReachHere,
bestTestingTargetIndex,
numTestingEgsCorrectClassUsingBestTestingIndex,
numTrainingEgsCorrectClassUsingBestTestingIndex);
// Update the tree statistics.
InternalNodes++;
// Now, attach the new internal node to the supplied node.
if (parent != null)
parent.setChild(arcNum, internalNode);
// Add a reference to the new node to the node list.
Nodes.Add(internalNode);
return internalNode;
}
/// <summary>
/// Attaches a new leaf node to the supplied node, along
/// the specified arc.
/// </summary>
public DecisionTreeNode addLeafNode(DecisionTreeNode parent,
int arcNum,
String label,
AttributeMask mask,
int numTrainingExamplesReachHere,
int bestTrainingTargetIndex,
int numTrainingEgsCorrectClassUsingBestTrainingIndex,
int numTestingEgsCorrectClassUsingBestTrainingIndex,
int numTestingExamplesReachHere,
int bestTestingTargetIndex,
int numTestingEgsCorrectClassUsingBestTestingIndex,
int numTrainingEgsCorrectClassUsingBestTestingIndex)
{
// Create new leaf node.
DecisionTreeNode leaf =
new DecisionTreeNode(parent, label, null, mask);
// Set the node statistics.
leaf.setTrainingStats(numTrainingExamplesReachHere,
bestTrainingTargetIndex,
numTrainingEgsCorrectClassUsingBestTrainingIndex,
numTestingEgsCorrectClassUsingBestTrainingIndex);
leaf.setTestingStats(numTestingExamplesReachHere,
bestTestingTargetIndex,
numTestingEgsCorrectClassUsingBestTestingIndex,
numTrainingEgsCorrectClassUsingBestTestingIndex);
// Update the tree statistics.
TrainingCorrect += numTrainingEgsCorrectClassUsingBestTrainingIndex;
TestingCorrect += numTestingEgsCorrectClassUsingBestTrainingIndex;
// Now, attach the new leaf to the supplied node.
if (parent != null)
parent.setChild(arcNum, leaf);
// Add a reference to the new node to the node list.
Nodes.Add(leaf);
// Determine if the tree is complete.
if (findIncompleteNode((DecisionTreeNode)Nodes[0], new int[1]) == null)
{
Complete = true;
}
return leaf;
}