example_linearmodel.cpp

 
#include <iostream>
#include <Pds/Ra>
#include <Pds/Ml>
        
int main(void)
{
    Pds::IterationConf Conf;
    Pds::Vector W;
    Pds::Vector Ypr;
        
    // Generating data
    unsigned int L=2000;
    Pds::Matrix X;
    Pds::Vector Y;
    Pds::DataSet::Regression::LoadDataLineOutlierRand(L,X,Y,1);
    
    // Split data set in {Training,Cross-validation,Test}
    Pds::DataSetBlock Dat=Pds::DataSet::Split(X,Y,4,2,2);
    
    // Create W using training data
    W=Pds::LinearModel::FittingNormalMeanSquare(Conf,Dat.Xtr,Dat.Ytr);
    if(Conf.LastIter>0) Conf.Print("\n");
    W.T().Print("\nW:\n");
    
    // Testing W with training data set
    Ypr=Pds::LinearModel::Predict(W,Dat.Xtr);
    std::cout<<"Training :: R2 : "<<Dat.Ytr.R2(Ypr)<<std::endl;
    
    // Testing W with training data set
    Ypr=Pds::LinearModel::Predict(W,Dat.Xtt);
    std::cout<<"Testing  :: R2 : "<<Dat.Ytt.R2(Ypr)<<std::endl;
    
    Pds::Octave::XLabel="x1";
    Pds::Octave::YLabel="x2";
    Pds::Octave::Plot::CurveXYXY(Dat.Xtt,Dat.Ytt,Dat.Xtt,Ypr,"testando.m","example_linearmodel.png");
    
    return 0;
}