example.h

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//
//    Omlet - Open Machine Learning Enhanced Toolkit
//
//    Copyright (C) 2014   TALP Research Center
//                         Universitat Politecnica de Catalunya
//
//    This file is part of the Omlet library
//
//    The Omlet library is free software; you can redistribute it 
//    and/or modify it under the terms of the GNU Affero General Public
//    License as published by the Free Software Foundation; either
//    version 3 of the License, or (at your option) any later version.
//
//    This library is distributed in the hope that it will be useful,
//    but WITHOUT ANY WARRANTY; without even the implied warranty of
//    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
//    Affero General Public License for more details.
//
//    You should have received a copy of the GNU Affero General Public
//    License along with this library; if not, write to the Free Software
//    Foundation, Inc., 51 Franklin St, 5th Floor, Boston, MA 02110-1301 USA
//
//    contact: Lluis Padro (padro@lsi.upc.es)
//             TALP Research Center
//             despatx Omega.S112 - Campus Nord UPC
//             08034 Barcelona.  SPAIN
//

//
// Author: Xavier Carreras
//

#ifndef _EXAMPLE
#define _EXAMPLE

#include <map>
#include <vector>

namespace freeling {


  class category {
    friend class example;
  protected:
    bool belongs;
    double weight;
    double prediction;   

  public:
    category(bool, double, double);
    category(const category &);
  };


  class example : public std::map<int,double> {

  private:
    int dimension;
    std::vector<category> labels;
    int nlabels;

  public:  
    example(int nl);
    example(const example &e);

    example(double f1, const example& i1, double f2, const example& i2);

    double norm() const;

    void add_feature(int l, double v = 1.0);

    int get_nlabels() const;
    double get_feature_value(int label) const;
    int get_dimension() const;

    double inner_product(const example &i2) const;
    void add_vector(double f, const example &i2);

    void set_label(int l, bool b, double w, double pr);
    void set_belongs(int l, bool b);
    bool belongs(int l) const;
    int sign(int l) const;
    void set_weight(int l, double w);
    double get_weight(int l) const;
    void set_prediction(int l, double pr);
    double get_prediction(int l) const;
  };

} // namespace

#endif