PLearn 0.1
BaseRegressorConfidence.h
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00001 // -*- C++ -*-
00002 
00003 // BaseRegressorConfidence.h
00004 // Copyright (c) 1998-2002 Pascal Vincent
00005 // Copyright (C) 1999-2002 Yoshua Bengio and University of Montreal
00006 // Copyright (c) 2002 Jean-Sebastien Senecal, Xavier Saint-Mleux, Rejean Ducharme
00007 //
00008 // Redistribution and use in source and binary forms, with or without
00009 // modification, are permitted provided that the following conditions are met:
00010 // 
00011 //  1. Redistributions of source code must retain the above copyright
00012 //     notice, this list of conditions and the following disclaimer.
00013 // 
00014 //  2. Redistributions in binary form must reproduce the above copyright
00015 //     notice, this list of conditions and the following disclaimer in the
00016 //     documentation and/or other materials provided with the distribution.
00017 // 
00018 //  3. The name of the authors may not be used to endorse or promote
00019 //     products derived from this software without specific prior written
00020 //     permission.
00021 // 
00022 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00023 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00024 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00025 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00026 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00027 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00028 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00029 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00030 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00031 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00032 // 
00033 // This file is part of the PLearn library. For more information on the PLearn
00034 // library, go to the PLearn Web site at www.plearn.org
00035 
00036 
00037 /* ********************************************************************************    
00038  * $Id: BaseRegressorConfidence.h, v 1.0 2004/07/19 10:00:00 Bengio/Kegl/Godbout   *
00039  * This file is part of the PLearn library.                                     *
00040  ******************************************************************************** */
00041 
00042 
00043 #ifndef BaseRegressorConfidence_INC
00044 #define BaseRegressorConfidence_INC
00045 
00046 #include <plearn_learners/generic/PLearner.h>
00047 #include <plearn/vmat/MeanImputationVMatrix.h>
00048 #include <plearn/base/stringutils.h>
00049 #include <plearn/math/BottomNI.h>
00050 
00051 namespace PLearn {
00052 using namespace std;
00053 
00054 class BaseRegressorConfidence: public PLearner
00055 {
00056     typedef PLearner inherited;
00057   
00058 private:
00059 
00060 /*
00061   Build options: they have to be set before training
00062 */
00063 
00064     int  number_of_neighbors;                // the number of nearest neighbors to consider
00065     real sigma;
00066     real raise_confidence;
00067     real lower_confidence;
00068   
00069 /*
00070   Learnt options: they are sized and initialized if need be, at stage 0
00071 */
00072 
00073     TMat<int> neighbors;
00074     TVec<real> nearest_neighbbors_target_mean;
00075  
00076 /*
00077   Work fields: they are sized and initialized if need be, at buid time
00078 */ 
00079  
00080     Vec input_to_search;
00081     Vec target_to_search;
00082     real weight_to_search;
00083     Vec input_to_compare;
00084     Vec target_to_compare;
00085     real weight_to_compare;
00086     real two_sigma_square;
00087     real root_two_pi_sigma_square;
00088    
00089   
00090 public:
00091     BaseRegressorConfidence();
00092     virtual              ~BaseRegressorConfidence();
00093     
00094     PLEARN_DECLARE_OBJECT(BaseRegressorConfidence);
00095 
00096     static  void         declareOptions(OptionList& ol);
00097     virtual void         makeDeepCopyFromShallowCopy(CopiesMap &copies);
00098     virtual void         build();
00099     virtual void         train();
00100     virtual void         forget();
00101     virtual int          outputsize() const;
00102     virtual TVec<string> getTrainCostNames() const;
00103     virtual TVec<string> getTestCostNames() const;
00104     virtual void         computeOutput(const Vec& input, Vec& output) const;
00105     virtual void         computeOutputAndCosts(const Vec& input, const Vec& target, Vec& output, Vec& costs) const;
00106     virtual void         computeCostsFromOutputs(const Vec& input, const Vec& output, const Vec& target, Vec& costs) const;
00107   
00108 private:
00109     void         build_();
00110     void         verbose(string msg, int level);
00111 };
00112 
00113 DECLARE_OBJECT_PTR(BaseRegressorConfidence);
00114 
00115 } // end of namespace PLearn
00116 
00117 #endif
00118 
00119 
00120 /*
00121   Local Variables:
00122   mode:c++
00123   c-basic-offset:4
00124   c-file-style:"stroustrup"
00125   c-file-offsets:((innamespace . 0)(inline-open . 0))
00126   indent-tabs-mode:nil
00127   fill-column:79
00128   End:
00129 */
00130 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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