// Budujemy drzewo
public TreeNode MountTree(List <List <int> > aSystem, List <Atrybut> aAtrybuty)
{
int decision;
if (AllDecisionOne(aSystem, out decision))
{
return(new TreeNode("decision: " + Convert.ToString(decision)));
}
if (aAtrybuty.Count == 0)
{
return(new TreeNode("decision: " + Convert.ToString(getMostCommonValue(aSystem))));
}
this.nNegatives = CountTotalNegatives(aSystem);
this.nPositives = aSystem.Count() - this.nNegatives;
this.dEntropy = GetEntropy(this.nPositives, this.nNegatives);
Atrybut oBestAtri = GetBestAtribute(aSystem, aAtrybuty);
TreeNode root = new TreeNode(oBestAtri.ToString());
foreach (int value in oBestAtri.aValues)
{
TreeNode subroot = root.AddTreeNode(new TreeNode("value: " + Convert.ToString(value)));
List <List <int> > aSystemC = new List <List <int> >();
List <Atrybut> aAtrybutyC = new List <Atrybut>();
//zbior obiektow zawierajacy atrybut - bez klonowania !
foreach (List <int> Obj in aSystem)
{
if (Obj[oBestAtri.nNumerKol] == value)
{
aSystemC.Add(Obj);
}
}
//atrybuty bez wybranego
foreach (Atrybut item in aAtrybuty)
{
if (item != oBestAtri)
{
aAtrybutyC.Add(item);
}
}
if (aSystemC.Count == 0)
{
return(new TreeNode("decision: " + Convert.ToString(getMostCommonValue(aSystemC))));
}
else
{
DecisionTree id3 = new DecisionTree();
TreeNode subtree = id3.MountTree(aSystemC, aAtrybutyC);
subroot.AddTreeNode(subtree);
}
}
return(root);
}
// Najlepszy atrybut z najlepsza metryka
private Atrybut GetBestAtribute(List <List <int> > aSystem, List <Atrybut> aAtrybuty)
{
double MaxGain = -999.9; // brak
Atrybut oBestAtr = null;
foreach (Atrybut atrybut in aAtrybuty)
{
double tmp = GetGain(aSystem, atrybut);
if (tmp > MaxGain)
{
MaxGain = tmp;
oBestAtr = atrybut;
}
}
return(oBestAtr);
}
private double GetGain(List <List <int> > aSystem, Atrybut atrybut)
{
double sum = 0.0;
int positives, negatives;
foreach (int value in atrybut.aValues)
{
positives = negatives = 0;
CountDecAtAtrByVal(aSystem, atrybut, value, out positives, out negatives);
double entropy = GetEntropy(positives, negatives);
double total = this.nPositives + this.nNegatives;
sum += -(double)(positives + negatives) / total * entropy;
}
return(this.dEntropy + sum);
}
// Zwracamy ile jest decyzji pozytywnych ile negatywnych dla obiektu o podanym atrybucie i wartosci
private void CountDecAtAtrByVal(List <List <int> > aSystem, Atrybut oAtrybut, int value, out int positives, out int negatives)
{
positives = negatives = 0;
foreach (List <int> Obj in aSystem)
{
if (Obj[oAtrybut.nNumerKol] == value)
{
if (Obj.Last() == 0)
{
negatives++;
}
else
{
positives++;
}
}
}
return;
}
