#ifndef RANKSVM_H
#define RANKSVM_H

#include<Eigen/Dense>
#include<string>
#include<list>
#include"../tools/dataProvider.h"
#include "../tools/easylogging++.h"

// Model File:
// Model type -> String
// Number of features (fsize) -> int
// Weight matrix size, (fsize,1) ->  (int,int)
// Weight vector
// beta

typedef struct SVMModel{
    Eigen::VectorXd weight;
    double beta;
} SVMModel;

class RSVM  //Virtual base class for all RSVM operations
{
protected:
    SVMModel model;
    int fsize;
public:
    virtual int train(DataList &D)=0;
    virtual int predict(DataList &D,std::vector<double> &res)=0;
    // TODO Not sure how to construct this
    //  Possible solution: generate a nxn matrix each row contains the sorted list of ranker result.
    int saveModel(const std::string fname);
    static RSVM* loadModel(const std::string fname);
    virtual std::string getName()=0;
    SVMModel getModel(){
        return model;};
    int setModel(const SVMModel &model);
};

extern double C;

#endif