public void TestDecisionTreeStructure()
{
IDecisionTreeNode first = new DecisionTreeLeafNode(2);
var tree = new DecisionTree(first);
AreEqual(2, tree.Classify(new[] { 1, 2, 3 }));
var tests = new IDecisionTreeNode[]
{
new DecisionTreeLeafNode(0), new DecisionTreeLeafNode(0),
new DecisionTreeLeafNode(1), new DecisionTreeLeafNode(2)
};
first = new DecisionTreeInternalNode(1, tests);
tree = new DecisionTree(first);
int[][] x = { new[] { 0, 0 }, new[] { 0, 1 }, new[] { 0, 2 } };
for (var i = 0; i < 3; i++)
{
AreEqual(x[i][1], tree.Classify(x[i]));
}
}
private static IDecisionTreeNode IterativeDichotomiser3(int[,] x, int[] y, List <int> attributes)
{
var distinctLabelCount = y.Distinct().Count();
if (x.Length == 0)
{
return(new DecisionTreeLeafNode(0));
}
switch (distinctLabelCount)
{
case 1:
return(new DecisionTreeLeafNode(y[0]));
default:
{
if (attributes.Count == 0)
{
return(new DecisionTreeLeafNode(MajorLabel(y, distinctLabelCount)));
}
var attributeTest = BestAttribute(x, y, attributes);
if (attributeTest == -1)
{
return(new DecisionTreeLeafNode(MajorLabel(y, distinctLabelCount)));
}
attributes.Remove(attributeTest);
var attributeStateCount = 0;
for (var i = 0; i < y.Length; i++)
{
if (x[i, attributeTest] > attributeStateCount)
{
attributeStateCount = x[i, attributeTest];
}
}
++attributeStateCount;
attributeStateCount = Math.Max(_discreteClasses * 2, attributeStateCount);
// Split data
var subX = new int[attributeStateCount][, ];
var subY = new int[attributeStateCount][];
var attributeSubXCount = new int[attributeStateCount];
for (var i = 0; i < y.Length; i++)
{
++attributeSubXCount[x[i, attributeTest]];
}
var attributeLength = x.Length / y.Length;
for (var i = 0; i < attributeStateCount; i++)
{
subX[i] = new int[attributeSubXCount[i], attributeLength];
subY[i] = new int[attributeSubXCount[i]];
}
var subXAttributeFormCount = new int[attributeStateCount];
for (var i = 0; i < y.Length; i++)
{
for (var j = 0; j < attributeLength; j++)
{
subX[x[i, attributeTest]][subXAttributeFormCount[x[i, attributeTest]], j] = x[i, j];
}
subY[x[i, attributeTest]][subXAttributeFormCount[x[i, attributeTest]]] = y[i];
++subXAttributeFormCount[x[i, attributeTest]];
}
// Create tests
var tests = new IDecisionTreeNode[attributeStateCount];
for (var i = 0; i < attributeStateCount; i++)
{
if (subX[i].Length == 0)
{
tests[i] = new DecisionTreeLeafNode(MajorLabel(y, distinctLabelCount));
}
else
{
tests[i] = IterativeDichotomiser3(subX[i], subY[i],
attributes.GetRange(0, attributes.Count));
}
}
IDecisionTreeNode root = new DecisionTreeInternalNode(attributeTest, tests);
return(root);
}
}
}
