/// <summary>
/// creates tree by all xy array and all variables
/// only internal use
/// </summary>
/// <param name="xy">train set</param>
/// <param name="nclasses">now works only with 2</param>
/// <param name="nvars"></param>
/// <param name="npoints"></param>
/// <param name="modNvars"></param>
/// <param name="vidxes"></param>
/// <returns></returns>
private static DecisionTree CreateTree(double[,] xy, int nclasses, int nvars, int npoints, int modNvars, int[] vidxes, int[] ridxes)
{
DecisionTree result;
try
{
int info;
alglib.decisionforest df;
alglib.dfreport rep;
alglib.dfbuildrandomdecisionforest(xy, npoints, modNvars, nclasses, 1, 1, out info, out df, out rep);
result = new DecisionTree();
result.Id = CreateId();
result.AlglibTree = df;
result.NClasses = nclasses;
result.NVars = nvars;
result.ModNvars = modNvars;
result.VarIndexes = vidxes;
result.RowIndexes = ridxes;
}
catch (Exception e)
{
Logger.Log(e);
throw;
}
return result;
}
public void AddTree(DecisionTree tree)
{
_batch.Add(tree);
}
public void AddTree(DecisionTree tree)
{
_batch.Add(tree);
}
