/// <summary>
/// Trains this leaf based on input DataSets for signal and background
/// </summary>
public void Train(DataSet signal, DataSet background)
{
nSignal = signal.Points.Count;
nBackground = background.Points.Count;
// Determines whether this is a final leaf or if it branches
bool branch = ChooseVariable(signal, background);
if (branch)
{
// Creates a branch
output1 = new Leaf();
output2 = new Leaf();
DataSet signalLeft = new DataSet(signal.Names);
DataSet signalRight = new DataSet(signal.Names);
DataSet backgroundLeft = new DataSet(background.Names);
DataSet backgroundRight = new DataSet(background.Names);
foreach (var dataPoint in signal.Points)
{
if (DoSplit(dataPoint))
{
signalLeft.AddDataPoint(dataPoint);
}
else
{
signalRight.AddDataPoint(dataPoint);
}
}
foreach (var dataPoint in background.Points)
{
if (DoSplit(dataPoint))
{
backgroundLeft.AddDataPoint(dataPoint);
}
else
{
backgroundRight.AddDataPoint(dataPoint);
}
}
//Console.WriteLine("Splitting sLeft: " + signalLeft.Points.Count + " sRight: " + signalRight.Points.Count
// + " bLeft: " + backgroundLeft.Points.Count + " bRight: " + backgroundRight.Points.Count);
// Trains each of the resulting leaves
output1.Train(signalLeft, backgroundLeft);
output2.Train(signalRight, backgroundRight);
}
// Do nothing more if it is not a branch
}
static public DataSet ReadDataSet(this BinaryReader br)
{
int nvar = br.ReadInt32();
var names = new string[nvar];
for (int i = 0; i < nvar; ++i)
{
names[i] = br.ReadString();
}
var dataset = new DataSet(names);
int size = br.ReadInt32();
for (int i = 0; i < size; ++i)
{
var dp = br.ReadDataPoint(nvar);
dataset.AddDataPoint(dp);
}
return(dataset);
}