PLearn 0.1
SequentialLearner.h
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00001 // -*- C++ -*-
00002 
00003 // SequentialLearner.h
00004 //
00005 // Copyright (C) 2003 Rejean Ducharme, Yoshua Bengio
00006 // Copyright (C) 2003 Pascal Vincent
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 #ifndef SEQUENTIAL_LEARNER
00039 #define SEQUENTIAL_LEARNER
00040 
00041 #include <plearn_learners/generic/PLearner.h>
00042 
00043 namespace PLearn {
00044 using namespace std;
00045 
00057 class SequentialLearner: public PLearner
00058 {
00059 public:
00060     typedef PLearner inherited;
00061 
00062 protected:  
00063     int last_train_t; 
00064     int last_call_train_t; 
00065     mutable int last_test_t; 
00066 
00067 public:
00068     int get_last_train_t(){ return last_train_t; }
00069     int get_last_call_train_t(){ return last_call_train_t; }
00070     int get_last_test_t(){ return last_test_t; }
00071   
00072 public:
00073   
00078     int init_train_size;
00079     int max_seq_len;    
00080     int max_train_len;  
00081     int train_step;     
00082     int horizon;        
00083     int outputsize_;
00084 
00087     Mat predictions; 
00088 
00089     Mat errors; 
00090 
00091 private:
00093     void build_();
00094   
00095 protected:
00097     static void declareOptions(OptionList& ol);
00098   
00099 public:
00100   
00102     SequentialLearner();
00103   
00105     virtual void build();
00106   
00108     virtual int outputsize() const;
00109 
00110     virtual int nTestCosts() const;
00111 
00112     virtual void setTrainingSet(VMat training_set, bool call_forget=true);
00113   
00123     virtual void train() =0;
00124  
00131     virtual void test(VMat testset, PP<VecStatsCollector> test_stats,
00132                       VMat testoutputs=0, VMat testcosts=0) const =0;
00133 
00134     virtual void computeOutputAndCosts(const Vec& input, const Vec& target,
00135                                        Vec& output, Vec& costs) const;
00136 
00137     virtual void computeCostsOnly(const Vec& input, const Vec& target,
00138                                   Vec& costs) const;
00139 
00140     virtual void computeOutput(const Vec& input, Vec& output) const;
00141 
00142     virtual void computeCostsFromOutputs(const Vec& input, const Vec& output,
00143                                          const Vec& target, Vec& costs) const;
00144 
00151     int sequenceStart() const { return init_train_size; }
00152     int sequenceLength() const { return last_test_t - init_train_size + 1; }
00153     Vec getCostSequence(int cost_index) const
00154     { return errors.subMat(sequenceStart(), cost_index, sequenceLength(), 1).toVecCopy(); }
00155     Vec getCostSequence(string cname) const 
00156     { return getCostSequence(getTestCostIndex(cname)); }
00157 
00163     virtual void matlabSave(const string& matlab_subdir);
00164   
00165     virtual void forget();
00166 
00169     PLEARN_DECLARE_ABSTRACT_OBJECT(SequentialLearner);
00170     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00171 };
00172 
00174 DECLARE_OBJECT_PTR(SequentialLearner);
00175 
00176 } // end of namespace PLearn
00177 
00178 #endif
00179 
00180 
00181 /*
00182   Local Variables:
00183   mode:c++
00184   c-basic-offset:4
00185   c-file-style:"stroustrup"
00186   c-file-offsets:((innamespace . 0)(inline-open . 0))
00187   indent-tabs-mode:nil
00188   fill-column:79
00189   End:
00190 */
00191 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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