test_decisiontree3.cpp

 
#include <iostream>
#include <Pds/Ra>
#include <Pds/Ml>
    
int main(void)
{
    Pds::IterationConf Conf;
    Conf.Show=false; Conf.SetMinError(1e-07);    Conf.SetAlpha(0.1);
    
    Pds::ClassificationMetrics Metrics;
    Pds::Vector Yp;
    
    // Load training data
    Pds::Matrix X(Pds::Ra::TextFormat,"../test/dataset/bloodtransfusion_x.txt");
    Pds::Vector Y(Pds::Ra::TextFormat,"../test/dataset/bloodtransfusion_y.txt");
    Pds::Vector Mean(X.Ncol()); 
    Pds::Vector Std(X.Ncol());
    std::cout<<"Pr(x=1):\t"<<Y.Mean()<<"\n";
    
    Pds::DataSetBlock   Dat;
    Dat=Pds::DataSet::SplitAndScaling(X,Y, 0.7, 0.0, 0.3,Std,Mean);
    //X.Print("X:\n");
    
    // Creando Arbol
    Pds::DecisionTree::Counter=0;
    Pds::DecisionTree Arbol("k2means",Conf,Dat.Xtr,Dat.Ytr,0.95,4);
    std::cout<<"Pds::DecisionTree::Counter: "<<Pds::DecisionTree::Counter<<std::endl;
    
    //Arbol.ExportDotFile("arbol.dot");
    //Pds::Ra::System("dot -Tpng -o arbol.dot.png arbol.dot");   
    
    // Predict training data
    Yp=Arbol.Predict(Dat.Xtt);
    
    // Metrics of training
    Metrics = Pds::ClassificationMetrics::Calculate(0.5,Yp,Dat.Ytt);
    Metrics.Print("\n");
    
    // Creando Arbol
    Pds::DecisionTree::Counter=0;
    Pds::DecisionTree Arbol2(Dat.Xtr,Dat.Ytr,0.95,4);
    std::cout<<"Pds::DecisionTree::Counter: "<<Pds::DecisionTree::Counter<<std::endl;
    
    // Predict training data
    Yp=Arbol2.Predict(Dat.Xtt);
    
    // Metrics of training
    Metrics = Pds::ClassificationMetrics::Calculate(0.5,Yp,Dat.Ytt);
    Metrics.Print("\n");
    
    return 0;
}