example_decisiontree_create2.cpp

 
#include <iostream>
#include <Pds/Ra>
#include <Pds/Ml>
    
int main(void)
{
    Pds::Octave::XLabel="x_1";
    Pds::Octave::YLabel="x_2";
    Pds::Vector Yp;
    Pds::IterationConf Conf;
    Conf.Show=false; Conf.SetMinError(1e-07);    Conf.SetAlpha(0.1);
    
    // Load training data
    unsigned int L=1000;
    Pds::Matrix X;
    Pds::Vector Y;
    Pds::DataSet::Classification::LoadDataBand2(L,X,Y);
    
    Pds::Octave::Plot::PointsX2DY(X,Y,"testando.m","example_decisiontree_create2_data.png");
    
    // Creando un arbol
    Pds::DecisionTree::Counter=0;
    Pds::DecisionTree Arbol1("k2means",Conf,X,Y,0.8,3,0);
    std::cout<<"Pds::DecisionTree::Counter: "<<Pds::DecisionTree::Counter<<std::endl;
    
    Arbol1.ExportDotFile("Arbol1.dot");
    
    // Predict arbol with training data
    Yp=Arbol1.Predict(X);
    
    Pds::Octave::Plot::PointsX2DY(X,Yp,"testando.m","example_decisiontree_create2_conf.png");
    
    // Creando un arbol
    Pds::DecisionTree Arbol2(Arbol1);
    Arbol1.MakeEmpty();
    
    Arbol2.ExportDotFile("Arbol2.dot");
    
    // Predict arbol with training data
    Yp=Arbol2.Predict(X);
    
    Pds::Octave::Plot::PointsX2DY(X,Yp,"testando.m","example_decisiontree_create2_copy.png"); 
 
    return 0;
}