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-rw-r--r--utils/synutils/maxent-3.0/maxent.h402
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diff --git a/utils/synutils/maxent-3.0/maxent.h b/utils/synutils/maxent-3.0/maxent.h
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-/*
- * $Id: maxent.h,v 1.1.1.1 2007/05/15 08:30:35 kyoshida Exp $
- */
-
-#ifndef __MAXENT_H_
-#define __MAXENT_H_
-
-#include <string>
-#include <vector>
-#include <list>
-#include <map>
-#include <algorithm>
-#include <iostream>
-#include <string>
-#include <cassert>
-#include "mathvec.h"
-
-#define USE_HASH_MAP // if you encounter errors with hash, try commenting out
- // this line. (the program will be a bit slower, though)
-#ifdef USE_HASH_MAP
-#include <ext/hash_map>
-#endif
-
-//
-// data format for each sample for training/testing
-//
-struct ME_Sample {
- public:
- ME_Sample() : label("") {};
- ME_Sample(const std::string& l) : label(l) {};
- void set_label(const std::string& l) { label = l; }
-
- // to add a binary feature
- void add_feature(const std::string& f) { features.push_back(f); }
-
- // to add a real-valued feature
- void add_feature(const std::string& s, const double d) {
- rvfeatures.push_back(std::pair<std::string, double>(s, d));
- }
-
- public:
- std::string label;
- std::vector<std::string> features;
- std::vector<std::pair<std::string, double> > rvfeatures;
-
- // obsolete
- void add_feature(const std::pair<std::string, double>& f) {
- rvfeatures.push_back(f); // real-valued features
- }
-};
-
-//
-// for those who want to use load_from_array()
-//
-typedef struct ME_Model_Data {
- char* label;
- char* feature;
- double weight;
-} ME_Model_Data;
-
-class ME_Model {
- public:
- void add_training_sample(const ME_Sample& s);
- int train();
- std::vector<double> classify(ME_Sample& s) const;
- bool load_from_file(const std::string& filename);
- bool save_to_file(const std::string& filename, const double th = 0) const;
- int num_classes() const { return _num_classes; }
- std::string get_class_label(int i) const { return _label_bag.Str(i); }
- int get_class_id(const std::string& s) const { return _label_bag.Id(s); }
- void get_features(
- std::list<std::pair<std::pair<std::string, std::string>, double> >& fl);
- void set_heldout(const int h, const int n = 0) {
- _nheldout = h;
- _early_stopping_n = n;
- };
- void use_l1_regularizer(const double v) { _l1reg = v; }
- void use_l2_regularizer(const double v) { _l2reg = v; }
- void use_SGD(int iter = 30, double eta0 = 1, double alpha = 0.85) {
- _optimization_method = SGD;
- SGD_ITER = iter;
- SGD_ETA0 = eta0;
- SGD_ALPHA = alpha;
- }
- bool load_from_array(const ME_Model_Data data[]);
- void set_reference_model(const ME_Model& ref_model) {
- _ref_modelp = &ref_model;
- };
- void clear();
-
- ME_Model() {
- _l1reg = _l2reg = 0;
- _nheldout = 0;
- _early_stopping_n = 0;
- _ref_modelp = NULL;
- _optimization_method = LBFGS;
- }
-
- public:
- // obsolete. just for downward compatibility
- int train(const std::vector<ME_Sample>& train);
-
- private:
- enum OPTIMIZATION_METHOD {
- LBFGS,
- OWLQN,
- SGD
- } _optimization_method;
- // OWLQN and SGD are available only for L1-regularization
-
- int SGD_ITER;
- double SGD_ETA0;
- double SGD_ALPHA;
-
- double _l1reg, _l2reg;
-
- struct Sample {
- int label;
- std::vector<int> positive_features;
- std::vector<std::pair<int, double> > rvfeatures;
- std::vector<double> ref_pd; // reference probability distribution
- bool operator<(const Sample& x) const {
- for (unsigned int i = 0; i < positive_features.size(); i++) {
- if (i >= x.positive_features.size()) return false;
- int v0 = positive_features[i];
- int v1 = x.positive_features[i];
- if (v0 < v1) return true;
- if (v0 > v1) return false;
- }
- return false;
- }
- };
-
- struct ME_Feature {
- enum {
- MAX_LABEL_TYPES = 255
- };
-
- // ME_Feature(const int l, const int f) : _body((l << 24) + f) {
- // assert(l >= 0 && l < 256);
- // assert(f >= 0 && f <= 0xffffff);
- // };
- // int label() const { return _body >> 24; }
- // int feature() const { return _body & 0xffffff; }
- ME_Feature(const int l, const int f) : _body((f << 8) + l) {
- assert(l >= 0 && l <= MAX_LABEL_TYPES);
- assert(f >= 0 && f <= 0xffffff);
- };
- int label() const { return _body & 0xff; }
- int feature() const { return _body >> 8; }
- unsigned int body() const { return _body; }
-
- private:
- unsigned int _body;
- };
-
- struct ME_FeatureBag {
-#ifdef USE_HASH_MAP
- typedef __gnu_cxx::hash_map<unsigned int, int> map_type;
-#else
- typedef std::map<unsigned int, int> map_type;
-#endif
- map_type mef2id;
- std::vector<ME_Feature> id2mef;
- int Put(const ME_Feature& i) {
- map_type::const_iterator j = mef2id.find(i.body());
- if (j == mef2id.end()) {
- int id = id2mef.size();
- id2mef.push_back(i);
- mef2id[i.body()] = id;
- return id;
- }
- return j->second;
- }
- int Id(const ME_Feature& i) const {
- map_type::const_iterator j = mef2id.find(i.body());
- if (j == mef2id.end()) {
- return -1;
- }
- return j->second;
- }
- ME_Feature Feature(int id) const {
- assert(id >= 0 && id < (int)id2mef.size());
- return id2mef[id];
- }
- int Size() const { return id2mef.size(); }
- void Clear() {
- mef2id.clear();
- id2mef.clear();
- }
- };
-
- struct hashfun_str {
- size_t operator()(const std::string& s) const {
- assert(sizeof(int) == 4 && sizeof(char) == 1);
- const int* p = reinterpret_cast<const int*>(s.c_str());
- size_t v = 0;
- int n = s.size() / 4;
- for (int i = 0; i < n; i++, p++) {
- // v ^= *p;
- v ^= *p << (4 * (i % 2)); // note) 0 <= char < 128
- }
- int m = s.size() % 4;
- for (int i = 0; i < m; i++) {
- v ^= s[4 * n + i] << (i * 8);
- }
- return v;
- }
- };
-
- struct MiniStringBag {
-#ifdef USE_HASH_MAP
- typedef __gnu_cxx::hash_map<std::string, int, hashfun_str> map_type;
-#else
- typedef std::map<std::string, int> map_type;
-#endif
- int _size;
- map_type str2id;
- MiniStringBag() : _size(0) {}
- int Put(const std::string& i) {
- map_type::const_iterator j = str2id.find(i);
- if (j == str2id.end()) {
- int id = _size;
- _size++;
- str2id[i] = id;
- return id;
- }
- return j->second;
- }
- int Id(const std::string& i) const {
- map_type::const_iterator j = str2id.find(i);
- if (j == str2id.end()) return -1;
- return j->second;
- }
- int Size() const { return _size; }
- void Clear() {
- str2id.clear();
- _size = 0;
- }
- map_type::const_iterator begin() const { return str2id.begin(); }
- map_type::const_iterator end() const { return str2id.end(); }
- };
-
- struct StringBag : public MiniStringBag {
- std::vector<std::string> id2str;
- int Put(const std::string& i) {
- map_type::const_iterator j = str2id.find(i);
- if (j == str2id.end()) {
- int id = id2str.size();
- id2str.push_back(i);
- str2id[i] = id;
- return id;
- }
- return j->second;
- }
- std::string Str(const int id) const {
- assert(id >= 0 && id < (int)id2str.size());
- return id2str[id];
- }
- int Size() const { return id2str.size(); }
- void Clear() {
- str2id.clear();
- id2str.clear();
- }
- };
-
- std::vector<Sample> _vs; // vector of training_samples
- StringBag _label_bag;
- MiniStringBag _featurename_bag;
- std::vector<double> _vl; // vector of lambda
- ME_FeatureBag _fb;
- int _num_classes;
- std::vector<double> _vee; // empirical expectation
- std::vector<double> _vme; // empirical expectation
- std::vector<std::vector<int> > _feature2mef;
- std::vector<Sample> _heldout;
- double _train_error; // current error rate on the training data
- double _heldout_error; // current error rate on the heldout data
- int _nheldout;
- int _early_stopping_n;
- std::vector<double> _vhlogl;
- const ME_Model* _ref_modelp;
-
- double heldout_likelihood();
- int conditional_probability(const Sample& nbs,
- std::vector<double>& membp) const;
- int make_feature_bag(const int cutoff);
- int classify(const Sample& nbs, std::vector<double>& membp) const;
- double update_model_expectation();
- int perform_QUASI_NEWTON();
- int perform_SGD();
- int perform_GIS(int C);
- std::vector<double> perform_LBFGS(const std::vector<double>& x0);
- std::vector<double> perform_OWLQN(const std::vector<double>& x0,
- const double C);
- double backtracking_line_search(const Vec& x0, const Vec& grad0,
- const double f0, const Vec& dx, Vec& x,
- Vec& grad1);
- double regularized_func_grad(const double C, const Vec& x, Vec& grad);
- double constrained_line_search(double C, const Vec& x0, const Vec& grad0,
- const double f0, const Vec& dx, Vec& x,
- Vec& grad1);
-
- void set_ref_dist(Sample& s) const;
- void init_feature2mef();
-
- double FunctionGradient(const std::vector<double>& x,
- std::vector<double>& grad);
- static double FunctionGradientWrapper(const std::vector<double>& x,
- std::vector<double>& grad);
-};
-
-#endif
-
-/*
- * $Log: maxent.h,v $
- * Revision 1.1.1.1 2007/05/15 08:30:35 kyoshida
- * stepp tagger, by Okanohara and Tsuruoka
- *
- * Revision 1.24 2006/08/21 17:30:38 tsuruoka
- * use MAX_LABEL_TYPES
- *
- * Revision 1.23 2006/07/25 13:19:53 tsuruoka
- * sort _vs[]
- *
- * Revision 1.22 2006/07/18 11:13:15 tsuruoka
- * modify comments
- *
- * Revision 1.21 2006/07/18 10:02:15 tsuruoka
- * remove sample2feature[]
- * speed up conditional_probability()
- *
- * Revision 1.20 2006/07/18 05:10:51 tsuruoka
- * add ref_dist
- *
- * Revision 1.19 2005/12/23 10:33:02 tsuruoka
- * support real-valued features
- *
- * Revision 1.18 2005/12/23 09:15:29 tsuruoka
- * modify _train to reduce memory consumption
- *
- * Revision 1.17 2005/10/28 13:02:34 tsuruoka
- * set_heldout(): add default value
- * Feature()
- *
- * Revision 1.16 2005/09/12 13:51:16 tsuruoka
- * Sample: list -> vector
- *
- * Revision 1.15 2005/09/12 13:27:10 tsuruoka
- * add add_training_sample()
- *
- * Revision 1.14 2005/04/27 11:22:27 tsuruoka
- * bugfix
- * ME_Sample: list -> vector
- *
- * Revision 1.13 2005/04/27 10:20:19 tsuruoka
- * MiniStringBag -> StringBag
- *
- * Revision 1.12 2005/04/27 10:00:42 tsuruoka
- * remove tmpfb
- *
- * Revision 1.11 2005/04/26 14:25:53 tsuruoka
- * add MiniStringBag, USE_HASH_MAP
- *
- * Revision 1.10 2004/10/04 05:50:25 tsuruoka
- * add Clear()
- *
- * Revision 1.9 2004/08/09 12:27:21 tsuruoka
- * change messages
- *
- * Revision 1.8 2004/08/04 13:55:19 tsuruoka
- * modify _sample2feature
- *
- * Revision 1.7 2004/07/29 05:51:13 tsuruoka
- * remove modeldata.h
- *
- * Revision 1.6 2004/07/28 13:42:58 tsuruoka
- * add AGIS
- *
- * Revision 1.5 2004/07/28 05:54:14 tsuruoka
- * get_class_name() -> get_class_label()
- * ME_Feature: bugfix
- *
- * Revision 1.4 2004/07/27 16:58:47 tsuruoka
- * modify the interface of classify()
- *
- * Revision 1.3 2004/07/26 17:23:46 tsuruoka
- * _sample2feature: list -> vector
- *
- * Revision 1.2 2004/07/26 15:49:23 tsuruoka
- * modify ME_Feature
- *
- * Revision 1.1 2004/07/26 13:10:55 tsuruoka
- * add files
- *
- * Revision 1.18 2004/07/22 08:34:45 tsuruoka
- * modify _sample2feature[]
- *
- * Revision 1.17 2004/07/21 16:33:01 tsuruoka
- * remove some comments
- *
- */
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