public Attribute SelectBestAtr(List <Attribute> attributeList)
{
List <double> atrGainRatio = new List <double>();
for (int i = 0; i < attributeList.Count; i++)
{
atrGainRatio.Add(ID3Helper.CalculateGain(AttributeInformation(DataProcessing(attributeList[i])), SetEntropy) / SplitInfo(DataProcessing(attributeList[i])));
}
int maxGainRatio = atrGainRatio.
Select((value, index) => new { Value = value, Index = index }).
Aggregate((a, b) => (a.Value > b.Value) ? a : b).
Index;
return(attributeList[maxGainRatio]);
}
public double SplitInfo(List <List <int> > atrData)
{
double splitInfo = 0;
foreach (List <int> valList in atrData)
{
splitInfo += ID3Helper.CalculateSplitInfo(valList.Sum(), DecisionValues.Values.Count);
}
if (splitInfo != 0)
{
return(splitInfo);
}
else
{
return(1.0);
}
}
public TreeNode ID3Algorithm(List <Attribute> attributeList, Attribute decisionValues)
{
TreeNode tn = new TreeNode();
List <object> dv = decisionValues.Values;
if (attributeList.Count == 0)
{
tn.decription = "Failure";
return(tn);
}
if (dv.Distinct().Count().Equals(1))
{
tn.decription = dv[0];
return(tn);
}
#region ATTRIBUTE SELECTION, SUBSET CREATION, RECURRENCE
DecisionValues = decisionValues;
SetEntropy = ID3Helper.InitSetEntropy(decisionValues);
Attribute selectedAtr = SelectBestAtr(attributeList);
List <object> distinctSelectedAtrVal = selectedAtr.Values.Distinct().OrderBy(x => x).ToList();
attributeList.Remove(selectedAtr);
for (int dObj = 0; dObj < distinctSelectedAtrVal.Count(); dObj++)
{
List <Attribute> subsetAtrLs = new List <Attribute>();
for (int i = 0; i < attributeList.Count; i++)
{
List <object> subsetVal = new List <object>();
for (int j = 0; j < attributeList[i].Values.Count; j++)
{
if (selectedAtr.Values[j].Equals(distinctSelectedAtrVal[dObj]))
{
subsetVal.Add(attributeList[i].Values[j]);
}
}
subsetAtrLs.Add(new Attribute(attributeList[i].Name, subsetVal));
}
Attribute subsetDec = new Attribute();
List <object> subsetDecVal = new List <object>();
for (int j = 0; j < decisionValues.Values.Count; j++)
{
if (selectedAtr.Values[j].Equals(distinctSelectedAtrVal[dObj]))
{
subsetDecVal.Add(decisionValues.Values[j]);
}
}
subsetDec.Name = decisionValues.Name;
subsetDec.Values = subsetDecVal;
tn.decription = selectedAtr.Name.ToString();
//tn.child.Add(ID3Algorithm(subsetAtrLs, subsetDec));
TreeNode childNode = ID3Algorithm(subsetAtrLs, subsetDec);
childNode.parentDescription = distinctSelectedAtrVal[dObj].ToString();
tn.child.Add(childNode);
}
#endregion
return(tn);
}
public double AttributeInformation(List <List <int> > atrData)
{
double atrInformation = 0;
foreach (List <int> valList in atrData)
{
atrInformation += ((double)valList.Sum() / DecisionValues.Values.Count) * ID3Helper.CalculateEntropy(valList);
}
return(atrInformation);
}