#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(RidList &D)=0;
    virtual int predict(RidList &D,std::vector<double> &res)=0;
    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;// Compensating & scaling
// Main terminating criteria
extern int maxiter; // max iteration count
extern double prec; // precision
// conjugate gradient
extern double cg_prec; // precision
extern int cg_maxiter; // not worth having a large number
extern int ls_maxiter;
// line search
extern double ls_prec; // precision
extern double ls_turb; // perturbation

#endif