public static void FindBetterParameter(LearningTable education_table, ref int index_of_parametr, ref string best_value_for_split, int inputs, int outputs)
{
index_of_parametr = 0;
best_value_for_split = "";
LearningClassInfo[] leftClassInf;
LearningClassInfo[] rightClassInf;
double entrValue = -100000;
for (int index = 0; index < inputs; index++)
{
education_table.QuickSortByParam(0, education_table.LearningData.Length - 1, index);
double average = 0;
for (int prevRowInd = 0, nextRowInd = 1; nextRowInd < education_table.LearningData.Length; prevRowInd++, nextRowInd++)
{
average = (education_table.LearningData[prevRowInd][index] + education_table.LearningData[nextRowInd][index]) / 2.0;
leftClassInf = education_table.ClassInfoInit(education_table, 0, nextRowInd);
rightClassInf = education_table.ClassInfoInit(education_table, nextRowInd, education_table.LearningClasses.Length);
double newEntrValue = EntrophyCalculator.Info(education_table) - EntrophyCalculator.EntrophyCalc(leftClassInf, rightClassInf);
if (newEntrValue > entrValue)
{
entrValue = newEntrValue;
index_of_parametr = index;
best_value_for_split = average.ToString();
}
for (int i = 0; i < leftClassInf.Length; i++)
{
leftClassInf[i].number_of_checked = 0;
rightClassInf[i].number_of_checked = 0;
}
}
}
}
public static double Info(LearningTable T)
{
double info = 0;
double P = 0;
LearningClassInfo[] classInfo = T.ClassInfoInit(T);
for (int i = 0; i < classInfo.Length; i++)
{
P = (double)classInfo[i].number_of_checked / T.LearningClasses.Length;
if (P != 0)
{
info += P * Math.Log(P, 2);
}
}
return(-1 * info);
}
public void LearningC4_5(LearningTable education_table, Node tree_node, int inputs, int outputs)
{
LearningClassInfo[] thisClassInfo = education_table.ClassInfoInit(education_table, 0, education_table.LearningClasses.Length);
int k = 0;
foreach (LearningClassInfo clinf in thisClassInfo)
{
if (clinf.number_of_checked >= 1)
{
k++;
}
}
if (k >= 2)
{
LearningTable left_table = new LearningTable();
LearningTable right_table = new LearningTable();
tree_node.is_leaf = false;
int index_of_parametr = 0;
string best_value_for_split = "";
TreeBuilder.FindBetterParameter(education_table, ref index_of_parametr, ref best_value_for_split, inputs, outputs);
tree_node.rule = new Rule();
tree_node.rule.index_of_param = index_of_parametr;
tree_node.rule.value = (float)Convert.ToDouble(best_value_for_split);
tree_node.left_child = new Node();
tree_node.right_child = new Node();
left_table.SplitLearningTable(education_table, tree_node.rule, ref left_table, ref right_table);
LearningC4_5(left_table, tree_node.left_child, inputs, outputs);
LearningC4_5(right_table, tree_node.right_child, inputs, outputs);
}
else
{
tree_node.is_leaf = true;
tree_node.rule = new Rule();
foreach (LearningClassInfo clinf in thisClassInfo)
{
if (clinf.number_of_checked > 0)
{
tree_node.rule.value = clinf.class_name;
}
}
}
}
