public void CalculateHieristicValue(ACO.DecisionComponent <Edge> Element)
{
iFourmi.DataMining.Data.Attribute xAttribute = this._dataset.Metadata.Attributes[Element.Element.ParentIndex];
iFourmi.DataMining.Data.Attribute yAttribute = this._dataset.Metadata.Attributes[Element.Element.ChildIndex];
//iFourmi.DataMining.Data.Attribute zAttribute = this._dataset.Metadata.Target;
double MI = 0;
double size = this._dataset.Size;
double xy = 0;
double x = 0;
double y = 0;
List <int> attributeIndexes2 = new List <int>();
attributeIndexes2.Add(xAttribute.Index);
attributeIndexes2.Add(yAttribute.Index);
List <int> valueIndexes2 = new List <int>();
valueIndexes2.Add(0);
valueIndexes2.Add(0);
for (int xi = 0; xi < xAttribute.Values.Length; xi++)
{
x = xAttribute.ValueCounts[xi];
x = x / size;
for (int yi = 0; yi < yAttribute.Values.Length; yi++)
{
y = yAttribute.ValueCounts[yi];
y = y / size;
valueIndexes2[0] = xi;
valueIndexes2[1] = yi;
xy = this._dataset.Filter(attributeIndexes2, valueIndexes2).Count;
xy = xy / size;
double value = xy * Math.Log(xy / (x * y));
if (!double.IsNaN(value) && !double.IsInfinity(value))
{
MI += value;
}
}
}
if (MI <= 0)
{
MI = 0;
}
Element.Heuristic = MI;
}
public void CalculateHieristicValue(ACO.DecisionComponent <Edge> Element)
{
iFourmi.DataMining.Data.Attribute xAttribute = this._dataset.Metadata.Attributes[Element.Element.ParentIndex];
iFourmi.DataMining.Data.Attribute yAttribute = this._dataset.Metadata.Attributes[Element.Element.ChildIndex];
iFourmi.DataMining.Data.Attribute zAttribute = this._dataset.Metadata.Target;
double CMI = 0;
double size = this._dataset.Size;
double xy_z = 0;
double x_z = 0;
double y_z = 0;
double xyz = 0;
double xz = 0;
double yz = 0;
double z = 0;
List <int> attributeIndexes3 = new List <int>();
attributeIndexes3.Add(xAttribute.Index);
attributeIndexes3.Add(yAttribute.Index);
attributeIndexes3.Add(zAttribute.Index);
List <int> valueIndexes3 = new List <int>();
valueIndexes3.Add(0);
valueIndexes3.Add(0);
valueIndexes3.Add(0);
List <int> attributeIndexes2 = new List <int>();
attributeIndexes2.Add(xAttribute.Index);
attributeIndexes2.Add(zAttribute.Index);
List <int> valueIndexes2 = new List <int>();
valueIndexes2.Add(0);
valueIndexes2.Add(0);
for (int zi = 0; zi < zAttribute.Values.Length; zi++)
{
double _cmi = 0;
for (int xi = 0; xi < xAttribute.Values.Length; xi++)
{
for (int yi = 0; yi < yAttribute.Values.Length; yi++)
{
z = zAttribute.ValueCounts[zi];
attributeIndexes2[0] = xAttribute.Index;
attributeIndexes2[1] = zAttribute.Index;
valueIndexes2[0] = xi;
valueIndexes2[1] = zi;
xz = this._dataset.Filter(attributeIndexes2, valueIndexes2).Count;
x_z = xz / z;
attributeIndexes2[0] = yAttribute.Index;
attributeIndexes2[1] = zAttribute.Index;
valueIndexes2[0] = yi;
valueIndexes2[1] = zi;
yz = this._dataset.Filter(attributeIndexes2, valueIndexes2).Count;
y_z = yz / z;
valueIndexes3[0] = xi;
valueIndexes3[1] = yi;
valueIndexes3[2] = zi;
xyz = this._dataset.Filter(attributeIndexes3, valueIndexes3).Count;
xy_z = xyz / z;
double value = xy_z * Math.Log(xy_z / (x_z * y_z));
if (!double.IsNaN(value) && !double.IsInfinity(value))
{
_cmi += value;
}
}
}
CMI += _cmi * (z / size);
}
Element.Heuristic = CMI;
}
public void CalculateHieristicValue(ACO.DecisionComponent <Edge> Element)
{
iFourmi.DataMining.Data.Attribute xAttribute = this._dataset.Metadata.Attributes[Element.Element.ParentIndex];
iFourmi.DataMining.Data.Attribute yAttribute = this._dataset.Metadata.Attributes[Element.Element.ChildIndex];
iFourmi.DataMining.Data.Attribute zAttribute = this._dataset.Metadata.Target;
double InformationGain = 0;
double size = this._dataset.Size;
double xy_z = 0;
double x_z = 0;
double y_z = 0;
double xyz = 0;
double xz = 0;
double yz = 0;
double z = 0;
List <int> attributeIndexes3 = new List <int>();
attributeIndexes3.Add(xAttribute.Index);
attributeIndexes3.Add(yAttribute.Index);
attributeIndexes3.Add(zAttribute.Index);
List <int> valueIndexes3 = new List <int>();
valueIndexes3.Add(0);
valueIndexes3.Add(0);
valueIndexes3.Add(0);
List <int> attributeIndexes2 = new List <int>();
attributeIndexes2.Add(xAttribute.Index);
attributeIndexes2.Add(zAttribute.Index);
List <int> valueIndexes2 = new List <int>();
valueIndexes2.Add(0);
valueIndexes2.Add(0);
for (int zi = 0; zi < zAttribute.Values.Length; zi++)
{
double baseEntropy = 0;
double entropy = 0;
double _information = 0;
z = zAttribute.ValueCounts[zi];
for (int yi = 0; yi < yAttribute.Values.Length; yi++)
{
attributeIndexes2[0] = yAttribute.Index;
attributeIndexes2[1] = zAttribute.Index;
valueIndexes2[0] = yi;
valueIndexes2[1] = zi;
yz = this._dataset.Filter(attributeIndexes2, valueIndexes2).Count;
y_z = yz / z;
//baseEntropy -= (y_z) * Math.Log(y_z);
baseEntropy -= (yz / size) * Math.Log(yz / size);
if (double.IsNaN(baseEntropy) || double.IsInfinity(baseEntropy))
{
baseEntropy = 1;
}
}
for (int xi = 0; xi < xAttribute.Values.Length; xi++)
{
double x = xAttribute.ValueCounts[xi];
for (int yi = 0; yi < yAttribute.Values.Length; yi++)
{
attributeIndexes2[0] = xAttribute.Index;
attributeIndexes2[1] = zAttribute.Index;
valueIndexes2[0] = xi;
valueIndexes2[1] = zi;
xz = this._dataset.Filter(attributeIndexes2, valueIndexes2).Count;
x_z = xz / z;
valueIndexes3[0] = xi;
valueIndexes3[1] = yi;
valueIndexes3[2] = zi;
xyz = this._dataset.Filter(attributeIndexes3, valueIndexes3).Count;
xy_z = xyz / z;
//double value = (xy_z / x_z) * Math.Log((xy_z / x_z));
double value = -(xyz / x) * Math.Log((xyz / x));
if (!double.IsNaN(value) && !double.IsInfinity(value))
{
entropy += (xyz / z) * value;
}
}
}
_information = baseEntropy - entropy;
InformationGain += _information * (z / size);
}
Element.Heuristic = InformationGain;
}
public Variable(iFourmi.DataMining.Data.Attribute attribute)
{
this._attribute = attribute;
}
internal Attribute Clone()
{
Data.Attribute clone = new Attribute(this._name, this._index);
return(clone);
}
