nearest_neighbours.cpp

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#include <shark/Data/SparseData.h>
#include <shark/ObjectiveFunctions/Loss/ZeroOneLoss.h>
#include <shark/Models/NearestNeighborClassifier.h>
#include <shark/Algorithms/NearestNeighbors/TreeNearestNeighbors.h>
#include <shark/Algorithms/NearestNeighbors/SimpleNearestNeighbors.h>
#include <shark/Models/Trees/KDTree.h>
#include <shark/Models/Kernels/LinearKernel.h>
 
#include <shark/Core/Timer.h>
#include <iostream>
using namespace shark;
using namespace std;
 
int main(int argc, char **argv) {
    LabeledData<RealVector,unsigned int> data;
    importSparseData(data, "cod-rna",0,8192);
    
    LabeledData<RealVector,unsigned int> mnist;
    importSparseData(mnist, "mnist",0,8192);
    //~ {
    //~ Timer time;
    //~ KDTree<RealVector> kdtree(data.inputs());
    //~ TreeNearestNeighbors<RealVector,unsigned int> algorithmKD(data,&kdtree);
    //~ NearestNeighborClassifier<RealVector> model(&algorithmKD, 10);
    //~ ZeroOneLoss<> loss;
    //~ double error = loss(data.labels(),model(data.inputs()));
    //~ double time_taken = time.stop();
        
    //~ cout <<  "kdtree: "<< time_taken <<" "<< error<<std::endl;
    //~ }
    
    {
    Timer time;
    LinearKernel<RealVector> euclideanKernel;
    SimpleNearestNeighbors<RealVector,unsigned int> simpleAlgorithm(data,&euclideanKernel);
    NearestNeighborClassifier<RealVector> model(&simpleAlgorithm, 10);
    ZeroOneLoss<> loss;
    double error = loss(data.labels(),model(data.inputs()));
    double time_taken = time.stop();
        
    cout <<  "brute-force: "<< time_taken <<" "<< error<<std::endl;
    }
    
    {
    Timer time;
    LinearKernel<RealVector> euclideanKernel;
    SimpleNearestNeighbors<RealVector,unsigned int> simpleAlgorithm(mnist,&euclideanKernel);
    NearestNeighborClassifier<RealVector> model(&simpleAlgorithm, 10);
    ZeroOneLoss<> loss;
    double error = loss(mnist.labels(),model(mnist.inputs()));
    double time_taken = time.stop();
        
    cout <<  "brute-force-mnist: "<< time_taken <<" "<< error<<std::endl;
    }
    
}