public void LearnParameters(DataMining.Data.Dataset dataset)
{
foreach (Variable variable in this._variables)
{
string desc = variable.ToString();
variable.CPT = new ConditionalProbabilityTable(desc, variable.GetCTPSize());
//if (cache.ContainsKey(desc))
// variable.CPT.LoadFormString(cache[desc]);
//else
//{
if (variable.Parents == null)
{
int rowIndex = 0;
DataMining.Data.Attribute attribute = dataset.Metadata.Target.Index == variable.Index ? dataset.Metadata.Target : dataset.Metadata.Attributes[variable.Index];
for (int valueIndex = 0; valueIndex < variable.Attribute.Values.Length; valueIndex++)
{
int indexExpression = valueIndex + 1;
int count = attribute.ValueCounts[valueIndex];
variable.CPT.Set(rowIndex, indexExpression, count);
rowIndex++;
}
}
else
{
List <int> attributeIndexes = new List <int>();
DataMining.Data.Attribute[] attributes = new DataMining.Data.Attribute[variable.Parents.Count + 1];
attributes[0] = variable.Attribute;
attributeIndexes.Add(variable.Attribute.Index);
if (variable.Parents != null)
{
int i = 1;
foreach (Variable parent in variable.Parents)
{
attributes[i] = parent.Attribute;
attributeIndexes.Add(parent.Attribute.Index);
i++;
}
}
int[] valuesPointers = new int[attributes.Length];
Stack <int> pointerStack = new Stack <int>();
int rowIndex = 0;
bool stop = false;
while (true)
{
int indexExpression = variable.GetIndexExpression(valuesPointers.ToArray());
int count = dataset.Filter(attributeIndexes, valuesPointers.ToList <int>()).Count;
variable.CPT.Set(rowIndex, indexExpression, count);
rowIndex++;
int attributePointer = valuesPointers.Length - 1;
while (true)
{
if (valuesPointers[attributePointer] == attributes[attributePointer].Values.Length - 1)
{
if (attributePointer == 0)
{
stop = true;
break;
}
valuesPointers[attributePointer] = 0;
attributePointer--;
}
else
{
valuesPointers[attributePointer]++;
break;
}
}
if (stop)
{
break;
}
}
//}
//cache[desc] = variable.CPT.ToString();
}
}
}
