public List <int> Predict(List <List <int> > X)
{
int numExamples = X.Count;
int numFeatures = numExamples != 0 ? X[0].Count : 0;
var yhat = new List <int>();
if (_stump == null || _stump.splitVariable == -1)
{
for (int i = 0; i < numExamples; i++)
{
yhat.Add(_stump.splitSat);
}
}
else if (subModel1 == null)
{
yhat = _stump.Predict(X);
}
else
{
var pred1 = subModel1.Predict(X.Where(x => x[_stump.splitVariable] > _stump.splitValue).ToList());
var pred0 = subModel0.Predict(X.Where(x => x[_stump.splitVariable] <= _stump.splitValue).ToList());
var pred1Index = 0;
var pred0Index = 0;
for (int i = 0; i < numExamples; i++)
{
if (X[i][_stump.splitVariable] > _stump.splitValue)
{
yhat.Add(pred1[pred1Index]);
pred1Index++;
}
else
{
yhat.Add(pred0[pred0Index]);
pred0Index++;
}
}
}
return(yhat.ToList());
}
public List <int> Predict(List <List <int> > X)
{
return(decisionTreeRoot.Predict(X));
}
