BALL  1.4.1
ldaModel.h
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00001 /* ldaModel.h
00002  * 
00003  * Copyright (C) 2009 Marcel Schumann
00004  * 
00005  * This file is part of QuEasy -- A Toolbox for Automated QSAR Model
00006  * Construction and Validation.
00007  * QuEasy is free software; you can redistribute it and/or modify
00008  * it under the terms of the GNU General Public License as published by
00009  * the Free Software Foundation; either version 3 of the License, or (at
00010  * your option) any later version.
00011  * 
00012  * QuEasy is distributed in the hope that it will be useful, but
00013  * WITHOUT ANY WARRANTY; without even the implied warranty of
00014  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
00015  * General Public License for more details.
00016  * 
00017  * You should have received a copy of the GNU General Public License
00018  * along with this program; if not, see <http://www.gnu.org/licenses/>.
00019  */
00020 
00021 // -*- Mode: C++; tab-width: 2; -*-
00022 // vi: set ts=2:
00023 //
00024 //
00025 
00026 #ifndef LDAMODEL
00027 #define LDAMODEL
00028 
00029 #ifndef CLASSIFICATION
00030 #include <BALL/QSAR/classificationModel.h>
00031 #endif
00032 
00033 #ifndef STATISTICS
00034 #include <BALL/QSAR/statistics.h>
00035 #endif
00036 
00037 namespace BALL{
00038   namespace QSAR {
00039 
00041     class BALL_EXPORT LDAModel : public ClassificationModel
00042     { 
00043       public:
00047         LDAModel(const QSARData& q);
00048 
00049         ~LDAModel();
00051         
00052         
00056         void train();
00057         
00058         Vector<double> predict(const vector<double>& substance, bool transform=1);
00059 
00060         void setParameters(vector<double>& v);
00061         
00062         vector<double> getParameters() const;
00063         
00064         void saveToFile(string filename);
00065         
00066         void readFromFile(string filename);
00068         
00069         
00070       private:
00075         Matrix<double> sigma_;
00076         
00077 
00078         double lambda_;       
00079 
00081         vector<Matrix<double> > mean_vectors_;
00083     };
00084   }
00085 }
00086 
00087 #endif //LDAMODEL
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