PLearn 0.1
SVMClassificationTorch.h
Go to the documentation of this file.
00001 // -*- C++ -*-
00002 
00003 // SVMClassificationTorch.h
00004 //
00005 // Copyright (C) 2005 Olivier Delalleau 
00006 // 
00007 // Redistribution and use in source and binary forms, with or without
00008 // modification, are permitted provided that the following conditions are met:
00009 // 
00010 //  1. Redistributions of source code must retain the above copyright
00011 //     notice, this list of conditions and the following disclaimer.
00012 // 
00013 //  2. Redistributions in binary form must reproduce the above copyright
00014 //     notice, this list of conditions and the following disclaimer in the
00015 //     documentation and/or other materials provided with the distribution.
00016 // 
00017 //  3. The name of the authors may not be used to endorse or promote
00018 //     products derived from this software without specific prior written
00019 //     permission.
00020 // 
00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00031 // 
00032 // This file is part of the PLearn library. For more information on the PLearn
00033 // library, go to the PLearn Web site at www.plearn.org
00034 
00035 /* *******************************************************      
00036  * $Id: SVMClassificationTorch.h 4849 2006-01-27 15:20:09Z tihocan $ 
00037  ******************************************************* */
00038 
00039 // Authors: Olivier Delalleau
00040 
00044 #ifndef SVMClassificationTorch_INC
00045 #define SVMClassificationTorch_INC
00046 
00047 #include <plearn_learners/generic/TorchLearner.h>
00048 #include <plearn/ker/Kernel.h>
00049 
00050 namespace PLearn {
00051 
00052 class SVMClassificationTorch: public TorchLearner {
00053 
00054 private:
00055 
00056     typedef TorchLearner inherited;
00057   
00058 protected:
00059 
00060     // *********************
00061     // * protected options *
00062     // *********************
00063 
00064 public:
00065 
00066     // ************************
00067     // * public build options *
00068     // ************************
00069 
00070     real C;
00071     real cache_size;
00072     Ker kernel;
00073     int iter_msg;
00074     bool output_the_class;
00075     bool target_01;
00076 
00077     // ****************
00078     // * Constructors *
00079     // ****************
00080 
00082     SVMClassificationTorch();
00083 
00084     // ********************
00085     // * PLearner methods *
00086     // ********************
00087 
00088 private: 
00089 
00091     void build_();
00092 
00093 protected: 
00094   
00096     static void declareOptions(OptionList& ol);
00097 
00098 public:
00099 
00100     // ************************
00101     // **** Object methods ****
00102     // ************************
00103 
00105     virtual void build();
00106 
00108     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00109 
00110     // Declares other standard object methods.
00111     PLEARN_DECLARE_OBJECT(SVMClassificationTorch);
00112 
00113     // **************************
00114     // **** PLearner methods ****
00115     // **************************
00116 
00119 //  virtual int outputsize() const;
00120 
00123 //  virtual void forget();
00124     
00127 //  virtual void train();
00128 
00130     virtual void computeOutput(const Vec& input, Vec& output) const;
00131 
00133     virtual void computeCostsFromOutputs(const Vec& input, const Vec& output, 
00134                                          const Vec& target, Vec& costs) const;
00135 
00137     virtual TVec<std::string> getTestCostNames() const;
00138 
00141     virtual TVec<std::string> getTrainCostNames() const;
00142 
00144     virtual void setTrainingSet(VMat training_set, bool call_forget = true);
00145 
00146     // *** SUBCLASS WRITING: ***
00147     // While in general not necessary, in case of particular needs 
00148     // (efficiency concerns for ex) you may also want to overload
00149     // some of the following methods:
00150     // virtual void computeOutputAndCosts(const Vec& input, const Vec& target, Vec& output, Vec& costs) const;
00151     // virtual void computeCostsOnly(const Vec& input, const Vec& target, Vec& costs) const;
00152     // virtual void test(VMat testset, PP<VecStatsCollector> test_stats, VMat testoutputs=0, VMat testcosts=0) const;
00153     // virtual int nTestCosts() const;
00154     // virtual int nTrainCosts() const;
00155     // virtual void resetInternalState();
00156     // virtual bool isStatefulLearner() const;
00157 
00158 };
00159 
00160 // Declares a few other classes and functions related to this class.
00161 DECLARE_OBJECT_PTR(SVMClassificationTorch);
00162   
00163 } // end of namespace PLearn
00164 
00165 #endif
00166 
00167 
00168 /*
00169   Local Variables:
00170   mode:c++
00171   c-basic-offset:4
00172   c-file-style:"stroustrup"
00173   c-file-offsets:((innamespace . 0)(inline-open . 0))
00174   indent-tabs-mode:nil
00175   fill-column:79
00176   End:
00177 */
00178 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines