public DecisionTree createTree()
{
if (data.checkIfPlain())
{
DecisionTree toReturn = new DecisionTree(0, "-1", "-1", data.DataValues[0].DataClass);
return(toReturn);
}
Tuple <int, string> split = data.findBestSplit();
string nodeSign;
if (data.DataValues[0].Attributes[split.Item1].isNumerical())
{
nodeSign = "<=";
}
else
{
nodeSign = "=";
}
DecisionTree node = new DecisionTree(split.Item1, nodeSign, split.Item2);
Tuple <DataSet, DataSet> newTables = data.splitTable(split.Item1, split.Item2);
Sprint left = new Sprint(newTables.Item1);
Sprint right = new Sprint(newTables.Item2);
node.addChild('l', left.createTree());
node.addChild('r', right.createTree());
return(node);
}
public void createTree(string trainingPath, string trainingName, char separator)
{
Globals.stopWatch.Start();
DataSet trainingSet = new DataSet(trainingPath + "\\" + trainingName + ".txt", separator, true);
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Training data set");
Globals.stopWatch.Start();
Sprint sprint = new Sprint(trainingSet);
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Sprint created");
Globals.stopWatch.Start();
DecisionTree tree = sprint.createTree();
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Tree created");
Globals.stopWatch.Start();
tree.saveToTxt(trainingPath, "Decision_Tree_" + trainingName);
Globals.stopWatch.Stop();
Globals.printElapsedTimeResetWatch(Globals.stopWatch.Elapsed, "Saving tree to file");
}
