example_anomaly_detection_gaussian.cpp

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

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

Para executar o programa:

./example_anomaly_detection_gaussian

Retornando por consola:

X.Size(): 10000 2
Mu:
1.9993438130135 2.9991585071564
Sigma:
0.25065509848827        -0.0021491969165038
-0.0021491969165038     0.24650951245711

Anomaly detection:
X:
2       3
-2      4
-1      4

P(X):
0.64029520150186
1.3391319908642e-15
1.4971038691836e-09

Clasification - data

Código example_anomaly_detection_gaussian.cpp:

 
#include <iostream>
#include <Pds/Ra>
#include <Pds/Ml>
    
int main(void)
{
    unsigned int L=10000;
    Pds::Matrix X;
    Pds::Matrix Mu;
    Pds::Matrix Sigma;
    Pds::Vector P;
    
    // X=[x1 x2]
    X=Pds::MergeHor({ 2+0.5*Pds::RandN(L,1) , 3+0.5*Pds::RandN(L,1) });
    
    Pds::Octave::XLabel="x1";
    Pds::Octave::YLabel="x2";
    Pds::Octave::Plot::PointsX2D(X,"testando.m","example_anomaly_detection_gaussian_data.png");
    
    Pds::AnomalyDetection::MGaussianDensityEstimation(X,Mu,Sigma);
    
    X.Size().Print("X.Size(): ");
    Mu.Print("Mu:\n");
    Sigma.Print("Sigma:\n");
    
    std::cout<<"\nAnomaly detection:\n";
    
    X=Pds::Matrix("2 3\n-2 4\n-1 4");
    X.Print("X:\n");
    
    P=Pds::AnomalyDetection::MGaussianPDF(X,Mu,Sigma);
    P.Print("\nP(X):\n");
    
    return 0;
}