00001 /*!@file Learn/GentleBoostBinary.H GentleBoost 2-Class Classifier */ 00002 // //////////////////////////////////////////////////////////////////// // 00003 // The iLab Neuromorphic Vision C++ Toolkit - Copyright (C) 2001 by the // 00004 // University of Southern California (USC) and the iLab at USC. // 00005 // See http://iLab.usc.edu for information about this project. // 00006 // //////////////////////////////////////////////////////////////////// // 00007 // Major portions of the iLab Neuromorphic Vision Toolkit are protected // 00008 // under the U.S. patent ``Computation of Intrinsic Perceptual Saliency // 00009 // in Visual Environments, and Applications'' by Christof Koch and // 00010 // Laurent Itti, California Institute of Technology, 2001 (patent // 00011 // pending; application number 09/912,225 filed July 23, 2001; see // 00012 // http://pair.uspto.gov/cgi-bin/final/home.pl for current status). // 00013 // //////////////////////////////////////////////////////////////////// // 00014 // This file is part of the iLab Neuromorphic Vision C++ Toolkit. // 00015 // // 00016 // The iLab Neuromorphic Vision C++ Toolkit is free software; you can // 00017 // redistribute it and/or modify it under the terms of the GNU General // 00018 // Public License as published by the Free Software Foundation; either // 00019 // version 2 of the License, or (at your option) any later version. // 00020 // // 00021 // The iLab Neuromorphic Vision C++ Toolkit is distributed in the hope // 00022 // that it will be useful, but WITHOUT ANY WARRANTY; without even the // 00023 // implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR // 00024 // PURPOSE. See the GNU General Public License for more details. // 00025 // // 00026 // You should have received a copy of the GNU General Public License // 00027 // along with the iLab Neuromorphic Vision C++ Toolkit; if not, write // 00028 // to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, // 00029 // Boston, MA 02111-1307 USA. // 00030 // //////////////////////////////////////////////////////////////////// // 00031 // 00032 // Primary maintainer for this file: Dan Parks <danielfp@usc.edu> 00033 // $HeadURL$ 00034 // $Id$ 00035 // 00036 00037 #ifndef GENTLEBOOSTBINARY_H_DEFINED 00038 #define GENTLEBOOSTBINARY_H_DEFINED 00039 00040 #include "Learn/DecisionTree.H" 00041 #include "Util/Assert.H" 00042 #include "Util/log.H" 00043 #include "Util/SortUtil.H" 00044 #include <limits> 00045 #include <math.h> 00046 #include <stdio.h> 00047 #include <iostream> 00048 #include <fstream> 00049 00050 class GentleBoostBinary 00051 { 00052 public: 00053 GentleBoostBinary(int maxTreeSize=1); 00054 // Two Class Boost 00055 std::vector<float> predict(const std::vector<std::vector<float> >& data); 00056 std::vector<float> predict(const std::vector<std::vector<float> >& data, std::vector<float> weights); 00057 void train(const std::vector<std::vector<float> >& data, const std::vector<int>& labels, int maxIters); 00058 void train(const std::vector<std::vector<float> >& data, const std::vector<int>& labels, int maxIters, std::vector<float>& predictions); 00059 //! Remove all training 00060 void clear(); 00061 //! Print underlying decision tree 00062 void printTree(); 00063 void writeTree(std::ostream& outstream); 00064 void readTree(std::istream& instream); 00065 00066 private: 00067 //! Number of times to allow the underlying decision tree to split during it's training 00068 int itsMaxTreeSize; 00069 std::deque<rutz::shared_ptr<DecisionNode> > itsNodes; 00070 std::vector<float> itsWeights; 00071 }; 00072 00073 #endif // GENTLEBOOSTBINARY_H_DEFINED
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