private void Run_Click(object sender, RoutedEventArgs e)
{
if (isLoad == true)
{
Attribute hair = new Attribute("HairColor", new string[] { "Black", "Gray", "Silver" });
Attribute height = new Attribute("Height", new string[] { "Short", "Medium", "High" });
Attribute weight = new Attribute("Weight", new string[] { "Light", "Medium", "Heavy" });
Attribute cream = new Attribute("Cream", new string[] { "Yes", "No" });
Attribute[] attributes = new Attribute[] { hair, height, weight, cream };
DataTable samples = datatable;
DecisionTree id3 = new DecisionTree();
TreeNode root = id3.mountTree(samples, "Result", attributes);
TreeNode root1 = root;
var decisiontree = new DecisionTree();
decisiontree.SearchRule(root);
RuleID3 = decisiontree.RuleID3;
int i = 1;
foreach (var rule in RuleID3)
{
ListRule.Add("Rule [" +i+ "]: IF {" + rule);
i++;
}
lvRule.ItemsSource = ListRule;
DecisionTree.printNode(root, " ");
tvDecisionTree.Items.Clear();
TreeViewItem item = new TreeViewItem();
item.Header = "Logical Tree";
DumpVisualTree(item, root1);
tvDecisionTree.Items.Add(item);
item.ExpandSubtree();
txtTree.Text = DecisionTree.TreeList;
}
else
MessageBox.Show("Data must load before run", "Error", MessageBoxButton.OK, MessageBoxImage.Error);
}
private TreeNode internalMountTree(DataTable samples, string targetAttribute, Attribute[] attributes)
{
if (allSamplesPositives(samples, targetAttribute) == true)
return new TreeNode(new Attribute(true));
if (allSamplesNegatives(samples, targetAttribute) == true)
return new TreeNode(new Attribute(false));
if (attributes.Length == 0)
return new TreeNode(new Attribute(getMostCommonValue(samples, targetAttribute)));
mTotal = samples.Rows.Count;
mTargetAttribute = targetAttribute;
mTotalPositives = countTotalPositives(samples);
mEntropySet = calcEntropy(mTotalPositives, mTotal - mTotalPositives);
Attribute bestAttribute = getBestAttribute(samples, attributes);
TreeNode root = new TreeNode(bestAttribute);
DataTable aSample = samples.Clone();
foreach (string value in bestAttribute.values)
{
aSample.Rows.Clear();
DataRow[] rows = samples.Select(bestAttribute.AttributeName + " = " + "'" + value + "'");
foreach (DataRow row in rows)
{
aSample.Rows.Add(row.ItemArray);
}
ArrayList aAttributes = new ArrayList(attributes.Length - 1);
for (int i = 0; i < attributes.Length; i++)
{
if (attributes[i].AttributeName != bestAttribute.AttributeName)
aAttributes.Add(attributes[i]);
}
if (aSample.Rows.Count == 0)
{
return new TreeNode(new Attribute(getMostCommonValue(aSample, targetAttribute)));
}
else
{
DecisionTree dc3 = new DecisionTree();
TreeNode ChildNode = dc3.mountTree(aSample, targetAttribute, (Attribute[])aAttributes.ToArray(typeof(Attribute)));
root.AddTreeNode(ChildNode, value);
}
}
return root;
}
