1 /** \page staticoctave Matlab/Octave静态接口函数参考
4 \section Features_sec Features
5 \arg \b load_features \verbatim sg('load_features', filename, feature_class, type, target[, size[, comp_features]]) \endverbatim
6 \arg \b save_features \verbatim sg('save_features', filename, type, target) \endverbatim
7 \arg \b clean_features \verbatim sg('clean_features', 'TRAIN|TEST') \endverbatim
8 \arg \b get_features \verbatim [features]=sg('get_features', 'TRAIN|TEST') \endverbatim
9 \arg \b add_features \verbatim sg('add_features', 'TRAIN|TEST', features[, DNABINFILE|<ALPHABET>]) \endverbatim
10 \arg \b add_multiple_features \verbatim sg('add_multiple_features', 'TRAIN|TEST', repetitions, features[, DNABINFILE|<ALPHABET>]) \endverbatim
11 \arg \b add_dotfeatures \verbatim sg('add_dotfeatures', 'TRAIN|TEST', features[, DNABINFILE|<ALPHABET>]) \endverbatim
12 \arg \b set_features \verbatim sg('set_features', 'TRAIN|TEST', features[, DNABINFILE|<ALPHABET>][, [from_position_list|slide_window], window size, [position_list|shift], skip) \endverbatim
13 \arg \b set_ref_features \verbatim sg('set_ref_features', 'TRAIN|TEST') \endverbatim
14 \arg \b del_last_features \verbatim sg('del_last_features', 'TRAIN|TEST') \endverbatim
15 \arg \b convert \verbatim sg('convert', 'TRAIN|TEST', from_class, from_type, to_class, to_type[, order, start, gap, reversed]) \endverbatim
16 \arg \b reshape \verbatim sg('reshape', 'TRAIN|TEST, num_feat, num_vec) \endverbatim
17 \arg \b load_labels \verbatim sg('load_labels', filename, 'TRAIN|TARGET') \endverbatim
18 \arg \b set_labels \verbatim sg('set_labels', 'TRAIN|TEST', labels) \endverbatim
19 \arg \b get_labels \verbatim [labels]=sg('get_labels', 'TRAIN|TEST') \endverbatim
21 \section Kernel_sec Kernel
22 \arg \b set_kernel_normalization \verbatim sg('set_kernel_normalization', IDENTITY|AVGDIAG|SQRTDIAG|FIRSTELEMENT|VARIANCE, size[, kernel-specific parameters]) \endverbatim
23 \arg \b set_kernel \verbatim sg('set_kernel', type, size[, kernel-specific parameters]) \endverbatim
24 \arg \b add_kernel \verbatim sg('add_kernel', weight, kernel-specific parameters) \endverbatim
25 \arg \b del_last_kernel \verbatim sg('del_last_kernel') \endverbatim
26 \arg \b init_kernel \verbatim sg('init_kernel', 'TRAIN|TEST') \endverbatim
27 \arg \b clean_kernel \verbatim sg('clean_kernel') \endverbatim
28 \arg \b save_kernel \verbatim sg('save_kernel', filename, 'TRAIN|TEST') \endverbatim
29 \arg \b get_kernel_matrix \verbatim [K]]=sg('get_kernel_matrix', ['TRAIN|TEST') \endverbatim
30 \arg \b set_WD_position_weights \verbatim sg('set_WD_position_weights', W[, 'TRAIN|TEST']) \endverbatim
31 \arg \b get_subkernel_weights \verbatim [W]=sg('get_subkernel_weights') \endverbatim
32 \arg \b set_subkernel_weights \verbatim sg('set_subkernel_weights', W) \endverbatim
33 \arg \b set_subkernel_weights_combined \verbatim sg('set_subkernel_weights_combined', W, idx) \endverbatim
34 \arg \b get_dotfeature_weights_combined \verbatim [W]=sg('get_dotfeature_weights_combined', 'TRAIN|TEST') \endverbatim
35 \arg \b set_dotfeature_weights_combined \verbatim sg('set_dotfeature_weights_combined', W, idx) \endverbatim
36 \arg \b set_last_subkernel_weights \verbatim sg('set_last_subkernel_weights', W) \endverbatim
37 \arg \b get_WD_position_weights \verbatim [W]=sg('get_WD_position_weights') \endverbatim
38 \arg \b get_last_subkernel_weights \verbatim [W]=sg('get_last_subkernel_weights') \endverbatim
39 \arg \b compute_by_subkernels \verbatim [W]=sg('compute_by_subkernels') \endverbatim
40 \arg \b init_kernel_optimization \verbatim sg('init_kernel_optimization') \endverbatim
41 \arg \b get_kernel_optimization \verbatim [W]=sg('get_kernel_optimization') \endverbatim
42 \arg \b delete_kernel_optimization \verbatim sg('delete_kernel_optimization') \endverbatim
43 \arg \b use_diagonal_speedup \verbatim sg('use_diagonal_speedup', '0|1') \endverbatim
44 \arg \b set_kernel_optimization_type \verbatim sg('set_kernel_optimization_type', 'FASTBUTMEMHUNGRY|SLOWBUTMEMEFFICIENT') \endverbatim
45 \arg \b set_solver \verbatim sg('set_solver', 'AUTO|CPLEX|GLPK|INTERNAL') \endverbatim
46 \arg \b set_constraint_generator \verbatim sg('set_constraint_generator', 'LIBSVM_ONECLASS|LIBSVM_MULTICLASS|LIBSVM|SVMLIGHT|LIGHT|GPBTSVM|MPDSVM|GNPPSVM|GMNPSVM') \endverbatim
47 \arg \b set_prior_probs \verbatim sg('set_prior_probs', 'pos probs, neg_probs') \endverbatim
48 \arg \b set_prior_probs_from_labels \verbatim sg('set_prior_probs_from_labels', 'labels') \endverbatim
49 \arg \b resize_kernel_cache \verbatim sg('resize_kernel_cache', size) \endverbatim
51 \section Distance_sec Distance
52 \arg \b set_distance \verbatim sg('set_distance', type, data type[, distance-specific parameters]) \endverbatim
53 \arg \b init_distance \verbatim sg('init_distance', 'TRAIN|TEST') \endverbatim
54 \arg \b get_distance_matrix \verbatim [D]=sg('get_distance_matrix') \endverbatim
56 \section Classifier_sec Classifier
57 \arg \b classify \verbatim [result]=sg('classify') \endverbatim
58 \arg \b svm_classify \verbatim [result]=sg('svm_classify') \endverbatim
59 \arg \b classify_example \verbatim [result]=sg('classify_example', feature_vector_index) \endverbatim
60 \arg \b svm_classify_example \verbatim [result]=sg('svm_classify_example', feature_vector_index) \endverbatim
61 \arg \b get_classifier \verbatim [bias, weights]=sg('get_classifier', [index in case of MultiClassSVM]) \endverbatim
62 \arg \b get_clustering \verbatim [radi, centers|merge_distances, pairs]=sg('get_clustering') \endverbatim
63 \arg \b new_svm \verbatim sg('new_svm', 'LIBSVM_ONECLASS|LIBSVM_MULTICLASS|LIBSVM|SVMLIGHT|LIGHT|SVMLIN|GPBTSVM|MPDSVM|GNPPSVM|GMNPSVM|SUBGRADIENTSVM|WDSVMOCAS|SVMOCAS|SVMSGD|SVMBMRM|SVMPERF|KERNELPERCEPTRON|PERCEPTRON|LIBLINEAR_LR|LIBLINEAR_L2|LDA|LPM|LPBOOST|SUBGRADIENTLPM|KNN') \endverbatim
64 \arg \b new_classifier \verbatim sg('new_classifier', 'LIBSVM_ONECLASS|LIBSVM_MULTICLASS|LIBSVM|SVMLIGHT|LIGHT|SVMLIN|GPBTSVM|MPDSVM|GNPPSVM|GMNPSVM|SUBGRADIENTSVM|WDSVMOCAS|SVMOCAS|SVMSGD|SVMBMRM|SVMPERF|KERNELPERCEPTRON|PERCEPTRON|LIBLINEAR_LR|LIBLINEAR_L2|LDA|LPM|LPBOOST|SUBGRADIENTLPM|KNN') \endverbatim
65 \arg \b new_regression \verbatim sg('new_regression', 'SVRLIGHT|LIBSVR|KRR') \endverbatim
66 \arg \b new_clustering \verbatim sg('new_clustering', 'KMEANS|HIERARCHICAL') \endverbatim
67 \arg \b load_classifier \verbatim [filename, type]=sg('load_classifier') \endverbatim
68 \arg \b save_classifier \verbatim sg('save_classifier', filename) \endverbatim
69 \arg \b get_num_svms \verbatim [number of SVMs in MultiClassSVM]=sg('get_num_svms') \endverbatim
70 \arg \b get_svm \verbatim [bias, alphas]=sg('get_svm', [index in case of MultiClassSVM]) \endverbatim
71 \arg \b set_svm \verbatim sg('set_svm', bias, alphas) \endverbatim
72 \arg \b set_linear_classifier \verbatim sg('set_linear_classifier', bias, w) \endverbatim
73 \arg \b get_svm_objective \verbatim [objective]=sg('get_svm_objective') \endverbatim
74 \arg \b compute_svm_primal_objective \verbatim [objective]=sg('compute_svm_primal_objective') \endverbatim
75 \arg \b compute_svm_dual_objective \verbatim [objective]=sg('compute_svm_dual_objective') \endverbatim
76 \arg \b compute_mkl_primal_objective \verbatim [objective]=sg('compute_mkl_primal_objective') \endverbatim
77 \arg \b compute_mkl_dual_objective \verbatim [objective]=sg('compute_mkl_dual_objective') \endverbatim
78 \arg \b compute_relative_mkl_duality_gap \verbatim [gap]=sg('compute_relative_mkl_duality_gap') \endverbatim
79 \arg \b compute_absolute_mkl_duality_gap \verbatim [gap]=sg('compute_absolute_mkl_duality_gap') \endverbatim
80 \arg \b do_auc_maximization \verbatim sg('do_auc_maximization', 'auc') \endverbatim
81 \arg \b set_perceptron_parameters \verbatim sg('set_perceptron_parameters', learnrate, maxiter) \endverbatim
82 \arg \b train_classifier \verbatim sg('train_classifier', [classifier-specific parameters]) \endverbatim
83 \arg \b train_regression \verbatim sg('train_regression') \endverbatim
84 \arg \b train_clustering \verbatim sg('train_clustering') \endverbatim
85 \arg \b svm_train \verbatim sg('svm_train', [classifier-specific parameters]) \endverbatim
86 \arg \b svm_test \verbatim sg('svm_test') \endverbatim
87 \arg \b svm_qpsize \verbatim sg('svm_qpsize', size) \endverbatim
88 \arg \b svm_max_qpsize \verbatim sg('svm_max_qpsize', size) \endverbatim
89 \arg \b svm_bufsize \verbatim sg('svm_bufsize', size) \endverbatim
90 \arg \b c \verbatim sg('c', C1[, C2]) \endverbatim
91 \arg \b svm_epsilon \verbatim sg('svm_epsilon', epsilon) \endverbatim
92 \arg \b svr_tube_epsilon \verbatim sg('svr_tube_epsilon', tube_epsilon) \endverbatim
93 \arg \b svm_nu \verbatim sg('svm_nu', nu) \endverbatim
94 \arg \b mkl_parameters \verbatim sg('mkl_parameters', weight_epsilon, C_MKL [, mkl_norm ]) \endverbatim
95 \arg \b svm_max_train_time \verbatim sg('svm_max_train_time', max_train_time) \endverbatim
96 \arg \b use_shrinking \verbatim sg('use_shrinking', enable_shrinking) \endverbatim
97 \arg \b use_batch_computation \verbatim sg('use_batch_computation', enable_batch_computation) \endverbatim
98 \arg \b use_linadd \verbatim sg('use_linadd', enable_linadd) \endverbatim
99 \arg \b svm_use_bias \verbatim sg('svm_use_bias', enable_bias) \endverbatim
100 \arg \b mkl_use_interleaved_optimization \verbatim sg('mkl_use_interleaved_optimization', enable_interleaved_optimization) \endverbatim
101 \arg \b krr_tau \verbatim sg('krr_tau', tau) \endverbatim
103 \section Preprocessors_sec Preprocessors
104 \arg \b add_preproc \verbatim sg('add_preproc', preproc[, preproc-specific parameters]) \endverbatim
105 \arg \b del_preproc \verbatim sg('del_preproc') \endverbatim
106 \arg \b attach_preproc \verbatim sg('attach_preproc', 'TRAIN|TEST', force) \endverbatim
107 \arg \b clean_preproc \verbatim sg('clean_preproc') \endverbatim
110 \arg \b new_hmm \verbatim sg('new_hmm', N, M) \endverbatim
111 \arg \b load_hmm \verbatim sg('load_hmm', filename) \endverbatim
112 \arg \b save_hmm \verbatim sg('save_hmm', filename[, save_binary]) \endverbatim
113 \arg \b get_hmm \verbatim [p, q, a, b]=sg('get_hmm') \endverbatim
114 \arg \b append_hmm \verbatim sg('append_hmm', p, q, a, b) \endverbatim
115 \arg \b append_model \verbatim sg('append_model', 'filename'[, base1, base2]) \endverbatim
116 \arg \b set_hmm \verbatim sg('set_hmm', p, q, a, b) \endverbatim
117 \arg \b set_hmm_as \verbatim sg('set_hmm_as', POS|NEG|TEST) \endverbatim
118 \arg \b chop \verbatim sg('chop', chop) \endverbatim
119 \arg \b pseudo \verbatim sg('pseudo', pseudo) \endverbatim
120 \arg \b load_defs \verbatim sg('load_defs', filename, init) \endverbatim
121 \arg \b hmm_classify \verbatim [result]=sg('hmm_classify') \endverbatim
122 \arg \b hmm_test \verbatim sg('hmm_test', output name[, ROC filename[, neglinear[, poslinear]]]) \endverbatim
123 \arg \b one_class_linear_hmm_classify \verbatim [result]=sg('one_class_linear_hmm_classify') \endverbatim
124 \arg \b one_class_hmm_test \verbatim sg('one_class_hmm_test', output name[, ROC filename[, linear]]) \endverbatim
125 \arg \b one_class_hmm_classify \verbatim [result]=sg('one_class_hmm_classify') \endverbatim
126 \arg \b one_class_hmm_classify_example \verbatim [result]=sg('one_class_hmm_classify_example', feature_vector_index) \endverbatim
127 \arg \b hmm_classify_example \verbatim [result]=sg('hmm_classify_example', feature_vector_index) \endverbatim
128 \arg \b output_hmm \verbatim sg('output_hmm') \endverbatim
129 \arg \b output_hmm_defined \verbatim sg('output_hmm_defined') \endverbatim
130 \arg \b hmm_likelihood \verbatim [likelihood]=sg('hmm_likelihood') \endverbatim
131 \arg \b likelihood \verbatim sg('likelihood') \endverbatim
132 \arg \b save_hmm_likelihood \verbatim sg('save_hmm_likelihood', filename[, save_binary]) \endverbatim
133 \arg \b get_viterbi_path \verbatim [path, likelihood]=sg('get_viterbi_path', dim) \endverbatim
134 \arg \b vit_def \verbatim sg('vit_def') \endverbatim
135 \arg \b vit \verbatim sg('vit') \endverbatim
136 \arg \b bw \verbatim sg('bw') \endverbatim
137 \arg \b bw_def \verbatim sg('bw_def') \endverbatim
138 \arg \b bw_trans \verbatim sg('bw_trans') \endverbatim
139 \arg \b linear_train \verbatim sg('linear_train') \endverbatim
140 \arg \b save_hmm_path \verbatim sg('save_hmm_path', filename[, save_binary]) \endverbatim
141 \arg \b convergence_criteria \verbatim sg('convergence_criteria', num_iterations, epsilon) \endverbatim
142 \arg \b normalize_hmm \verbatim sg('normalize_hmm', [keep_dead_states]) \endverbatim
143 \arg \b add_states \verbatim sg('add_states', states, value) \endverbatim
144 \arg \b permutation_entropy \verbatim sg('permutation_entropy', width, seqnum) \endverbatim
145 \arg \b relative_entropy \verbatim [result]=sg('relative_entropy') \endverbatim
146 \arg \b entropy \verbatim [result]=sg('entropy') \endverbatim
147 \arg \b set_feature_matrix \verbatim sg('set_feature_matrix', features) \endverbatim
148 \arg \b set_feature_matrix_sparse \verbatim sg('set_feature_matrix_sparse', sp1, sp2) \endverbatim
149 \arg \b new_plugin_estimator \verbatim sg('new_plugin_estimator', pos_pseudo, neg_pseudo) \endverbatim
150 \arg \b train_estimator \verbatim sg('train_estimator') \endverbatim
151 \arg \b test_estimator \verbatim sg('test_estimator') \endverbatim
152 \arg \b plugin_estimate_classify_example \verbatim [result]=sg('plugin_estimate_classify_example', feature_vector_index) \endverbatim
153 \arg \b plugin_estimate_classify \verbatim [result]=sg('plugin_estimate_classify') \endverbatim
154 \arg \b set_plugin_estimate \verbatim sg('set_plugin_estimate', emission_probs, model_sizes) \endverbatim
155 \arg \b get_plugin_estimate \verbatim [emission_probs, model_sizes]=sg('get_plugin_estimate') \endverbatim
157 \section Structure_sec Structure
158 \arg \b best_path \verbatim sg('best_path', from, to) \endverbatim
159 \arg \b best_path_2struct \verbatim [prob, path, pos]=sg('best_path_2struct', p, q, cmd_trans, seq, pos, genestr, penalties, penalty_info, nbest, content_weights, segment_sum_weights) \endverbatim
160 \arg \b set_plif_struct \verbatim sg('set_plif_struct', id, name, limits, penalties, transform, min_value, max_value, use_cache, use_svm) \endverbatim
161 \arg \b get_plif_struct \verbatim [id, name, limits, penalties, transform, min_value, max_value, use_cache, use_svm]=sg('get_plif_struct') \endverbatim
162 \arg \b precompute_subkernels \verbatim sg('precompute_subkernels') \endverbatim
163 \arg \b precompute_content_svms \verbatim sg('precompute_content_svms', sequence, position_list, weights) \endverbatim
164 \arg \b get_lin_feat \verbatim [lin_feat]=sg('get_lin_feat') \endverbatim
165 \arg \b set_lin_feat \verbatim sg('set_lin_feat', lin_feat) \endverbatim
166 \arg \b init_dyn_prog \verbatim sg('init_dyn_prog', num_svms) \endverbatim
167 \arg \b init_intron_list \verbatim sg('init_intron_list', start_positions, end_positions, quality) \endverbatim
168 \arg \b precompute_tiling_features \verbatim sg('precompute_tiling_features', intensities, probe_pos, tiling_plif_ids) \endverbatim
169 \arg \b long_transition_settings \verbatim sg('long_transition_settings', use_long_transitions, threshold, max_len) \endverbatim
170 \arg \b set_model \verbatim sg('set_model', content_weights, transition_pointers, use_orf, mod_words) \endverbatim
171 \arg \b best_path_trans \verbatim [prob, path, pos]=sg('best_path_trans', p, q, nbest, seq_path, a_trans, segment_loss) \endverbatim
172 \arg \b best_path_trans_deriv \verbatim [p_deriv, q_deriv, cmd_deriv, penalties_deriv, my_scores, my_loss]=sg('best_path_trans_deriv', , my_path, my_pos, p, q, cmd_trans, seq, pos, genestr, penalties, state_signals, penalty_info, dict_weights, mod_words [, segment_loss, segmend_ids_mask]) \endverbatim
174 \section POIM_sec POIM
175 \arg \b compute_poim_wd \verbatim [W]=sg('compute_poim_wd', max_order, distribution) \endverbatim
176 \arg \b get_SPEC_consensus \verbatim [W]=sg('get_SPEC_consensus') \endverbatim
177 \arg \b get_SPEC_scoring \verbatim [W]=sg('get_SPEC_scoring', max_order) \endverbatim
178 \arg \b get_WD_consensus \verbatim [W]=sg('get_WD_consensus') \endverbatim
179 \arg \b get_WD_scoring \verbatim [W]=sg('get_WD_scoring', max_order) \endverbatim
181 \section Utility_sec Utility
182 \arg \b crc \verbatim [crc32]=sg('crc', string) \endverbatim
183 \arg \b ! \verbatim sg('!', system_command) \endverbatim
184 \arg \b exit \verbatim sg('exit') \endverbatim
185 \arg \b quit \verbatim sg('quit') \endverbatim
186 \arg \b exec \verbatim sg('exec', filename) \endverbatim
187 \arg \b set_output \verbatim sg('set_output', 'STDERR|STDOUT|filename') \endverbatim
188 \arg \b set_threshold \verbatim sg('set_threshold', threshold) \endverbatim
189 \arg \b init_random \verbatim sg('init_random', value_to_initialize_RNG_with) \endverbatim
190 \arg \b threads \verbatim sg('threads', num_threads) \endverbatim
191 \arg \b translate_string \verbatim [translation]=sg('translate_string', string, order, start) \endverbatim
192 \arg \b clear \verbatim sg('clear') \endverbatim
193 \arg \b tic \verbatim sg('tic') \endverbatim
194 \arg \b toc \verbatim sg('toc') \endverbatim
195 \arg \b print \verbatim sg('print', msg) \endverbatim
196 \arg \b echo \verbatim sg('echo', level) \endverbatim
197 \arg \b loglevel \verbatim sg('loglevel', 'ALL|DEBUG|INFO|NOTICE|WARN|ERROR|CRITICAL|ALERT|EMERGENCY') \endverbatim
198 \arg \b syntax_highlight \verbatim sg('syntax_highlight', 'ON|OFF') \endverbatim
199 \arg \b progress \verbatim sg('progress', 'ON|OFF') \endverbatim
200 \arg \b get_version \verbatim [version]=sg('get_version') \endverbatim
201 \arg \b help \verbatim sg('help') \endverbatim
202 \arg \b whos \verbatim sg('whos') \endverbatim
203 \arg \b run_python \verbatim [results]=sg('run_python', 'Var1', Var1, 'Var2', Var2,..., python_function) \endverbatim
204 \arg \b run_octave \verbatim [results]=sg('run_octave', 'Var1', Var1, 'Var2', Var2,..., octave_function) \endverbatim
205 \arg \b run_r \verbatim [results]=sg('run_r', 'Var1', Var1, 'Var2', Var2,..., r_function) \endverbatim
