example_predictor_evaluate.cpp

Programa para el testeo de las funciones.Para compilar o código example_predictor_evaluate.cpp:

g++ -static -o example_predictor_evaluate example_predictor_evaluate.cpp -lpdsmlmm 

Para executar o programa:

./example_predictor_evaluate

Retornando por consola:

W:
-0.00016956747675257    0.99510037048118

Training :: R2 : 0.96912476229416

Testing  :: R2 : 0.97149469355756

Clasification - data

Clasification - training

Clasification - testing

Código example_predictor_evaluate.cpp:

 
#include <iostream>
#include <Pds/Ra>
#include <Pds/Ml>
 
    
int main(void)
{
    Pds::Vector Yp;
    Pds::IterationConf Conf;
    
    // Generating data
    unsigned int L=1000;
    Pds::Matrix X;
    Pds::Vector Y;
    Pds::DataSet::Regression::LoadDataLine(L,X,Y);
    
    Pds::Octave::Plot::PointsXY(X,Y,"testando.m","example_predictor_evaluate_data.png");
    
    // Create Predictor
    Pds::Predictor Data(Conf,X,Y);
    Data.Print("W:\n");
    
    // Evaluate training data
    Yp=Data.Evaluate(X);
    
    // Testing W with training data set
    std::cout<<"\nTraining :: R2 : "<<Y.R2(Yp)<<std::endl;
    
    Pds::Octave::Plot::PointsXYXY(X,Y,X,Yp,"testando.m","example_predictor_evaluate_training.png");
    
    // Evaluate testing data
    Pds::DataSet::Regression::LoadDataLine(L,X,Y);
    Yp=Data.Evaluate(X);
    
    // Testing W with training data set
    std::cout<<"\nTesting  :: R2 : "<<Y.R2(Yp)<<std::endl;
    
    Pds::Octave::Plot::PointsXYXY(X,Y,X,Yp,"testando.m","example_predictor_evaluate_testing.png");
    return 0;
}