LinearRegressor.h

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// -*- C++ -*-

// LinearRegressor.h
//
// Copyright (C) 2003  Yoshua Bengio 
// 
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
// 
//  1. Redistributions of source code must retain the above copyright
//     notice, this list of conditions and the following disclaimer.
// 
//  2. Redistributions in binary form must reproduce the above copyright
//     notice, this list of conditions and the following disclaimer in the
//     documentation and/or other materials provided with the distribution.
// 
//  3. The name of the authors may not be used to endorse or promote
//     products derived from this software without specific prior written
//     permission.
// 
// THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
// NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
// 
// This file is part of the PLearn library. For more information on the PLearn
// library, go to the PLearn Web site at www.plearn.org

/* *******************************************************      
   * $Id: LinearRegressor.h,v 1.6 2004/07/21 20:27:27 tihocan Exp $
   ******************************************************* */

#ifndef LinearRegressor_INC
#define LinearRegressor_INC

#include <plearn_learners/generic/PLearner.h>

namespace PLearn {
using namespace std;

class LinearRegressor: public PLearner
{

private:
    
  typedef PLearner inherited;

  // Global storage used to save memory allocations.
  mutable Vec extendedinput; 
  mutable Vec input; 
  Vec target;
  Vec train_costs;

protected:
  // local variables
  Mat XtX; 
  Mat XtY; 
  real sum_squared_y; 
  real sum_gammas; 

  // *********************
  // * protected options *
  // *********************

  // ### declare protected option fields (such as learnt parameters) here
  
  Mat weights; 
  real weights_norm; 

public:

  // ************************
  // * public build options *
  // ************************

  bool cholesky;
  real weight_decay; 

  // ****************
  // * Constructors *
  // ****************

  // Default constructor, make sure the implementation in the .cc
  // initializes all fields to reasonable default values.
  LinearRegressor();


  // ******************
  // * PLearner methods *
  // ******************

private: 
  void build_();

protected: 
  static void declareOptions(OptionList& ol);

public:

  // ************************
  // **** Object methods ****
  // ************************

  virtual void build();

  virtual void makeDeepCopyFromShallowCopy(map<const void*, void*>& copies);

  // Declares other standard object methods
  //  If your class is not instantiatable (it has pure virtual methods)
  // you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT_METHODS 
  PLEARN_DECLARE_OBJECT(LinearRegressor);


  // **************************
  // **** PLearner methods ****
  // **************************

  virtual int outputsize() const;

  virtual void forget();

    
  virtual void train();


  virtual void computeOutput(const Vec& input, Vec& output) const;

  virtual void computeCostsFromOutputs(const Vec& input, const Vec& output, 
                                       const Vec& target, Vec& costs) const;
                                

  virtual TVec<string> getTestCostNames() const;

  virtual TVec<string> getTrainCostNames() const;


  // *** SUBCLASS WRITING: ***
  // While in general not necessary, in case of particular needs 
  // (efficiency concerns for ex) you may also want to overload
  // some of the following methods:
  // virtual void computeOutputAndCosts(const Vec& input, const Vec& target, Vec& output, Vec& costs) const;
  // virtual void computeCostsOnly(const Vec& input, const Vec& target, Vec& costs) const;
  // virtual void test(VMat testset, PP<VecStatsCollector> test_stats, VMat testoutputs=0, VMat testcosts=0) const;
  // virtual int nTestCosts() const;
  // virtual int nTrainCosts() const;

};

// Declares a few other classes and functions related to this class
  DECLARE_OBJECT_PTR(LinearRegressor);
  
} // end of namespace PLearn

#endif

---