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1 /* |
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2 |
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3 Copyright (c) 2007-2011 The LIBLINEAR Project. |
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4 Copyright (c) 2010,2015 Alois Schloegl <alois.schloegl@ist.ac.at> |
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5 This function is part of the NaN-toolbox |
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6 http://pub.ist.ac.at/~schloegl/matlab/NaN/ |
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7 |
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8 This code was extracted from liblinear-1.8 in Apr 2015 and |
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9 modified for the use with Octave |
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10 |
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11 This program is free software; you can redistribute it and/or modify |
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12 it under the terms of the GNU General Public License as published by |
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13 the Free Software Foundation; either version 3 of the License, or |
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14 (at your option) any later version. |
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15 |
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16 This program is distributed in the hope that it will be useful, |
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17 but WITHOUT ANY WARRANTY; without even the implied warranty of |
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18 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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19 GNU General Public License for more details. |
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20 |
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21 You should have received a copy of the GNU General Public License |
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22 along with this program; if not, see <http://www.gnu.org/licenses/>. |
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23 |
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24 */ |
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25 |
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26 #ifndef _LIBLINEAR_H |
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27 #define _LIBLINEAR_H |
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28 |
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29 #ifdef __cplusplus |
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30 extern "C" { |
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31 #endif |
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32 |
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33 struct feature_node |
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34 { |
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35 int index; |
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36 double value; |
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37 }; |
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38 |
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39 struct problem |
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40 { |
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41 int l, n; |
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42 int *y; |
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43 struct feature_node **x; |
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44 double bias; /* < 0 if no bias term */ |
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45 }; |
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46 |
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47 enum { L2R_LR, L2R_L2LOSS_SVC_DUAL, L2R_L2LOSS_SVC, L2R_L1LOSS_SVC_DUAL, MCSVM_CS, L1R_L2LOSS_SVC, L1R_LR, L2R_LR_DUAL }; /* solver_type */ |
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48 |
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49 struct parameter |
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50 { |
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51 int solver_type; |
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52 |
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53 /* these are for training only */ |
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54 double eps; /* stopping criteria */ |
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55 double C; |
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56 int nr_weight; |
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57 int *weight_label; |
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58 double* weight; |
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59 }; |
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60 |
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61 struct model |
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62 { |
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63 struct parameter param; |
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64 int nr_class; /* number of classes */ |
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65 int nr_feature; |
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66 double *w; |
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67 int *label; /* label of each class */ |
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68 double bias; |
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69 }; |
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70 |
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71 struct model* train(const struct problem *prob, const struct parameter *param); |
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72 void cross_validation(const struct problem *prob, const struct parameter *param, int nr_fold, int *target); |
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73 |
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74 int predict_values(const struct model *model_, const struct feature_node *x, double* dec_values); |
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75 int predict(const struct model *model_, const struct feature_node *x); |
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76 int predict_probability(const struct model *model_, const struct feature_node *x, double* prob_estimates); |
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77 |
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78 int save_model(const char *model_file_name, const struct model *model_); |
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79 struct model *load_model(const char *model_file_name); |
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80 |
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81 int get_nr_feature(const struct model *model_); |
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82 int get_nr_class(const struct model *model_); |
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83 void get_labels(const struct model *model_, int* label); |
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84 |
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85 void free_model_content(struct model *model_ptr); |
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86 void free_and_destroy_model(struct model **model_ptr_ptr); |
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87 void destroy_param(struct parameter *param); |
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88 |
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89 const char *check_parameter(const struct problem *prob, const struct parameter *param); |
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90 int check_probability_model(const struct model *model); |
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91 void set_print_string_function(void (*print_func) (const char*)); |
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92 |
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93 #ifdef __cplusplus |
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94 } |
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95 #endif |
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96 |
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97 #endif /* _LIBLINEAR_H */ |
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98 |
