Lines Matching refs:CvMat
197 CvNormalBayesClassifier( const CvMat* trainData, const CvMat* responses,
198 const CvMat* varIdx=0, const CvMat* sampleIdx=0 );
200 virtual bool train( const CvMat* trainData, const CvMat* responses,
201 const CvMat* varIdx = 0, const CvMat* sampleIdx=0, bool update=false );
203 virtual float predict( const CvMat* samples, CV_OUT CvMat* results=0, CV_OUT CvMat* results_prob=0 ) const;
218 CvMat* var_idx;
219 CvMat* cls_labels;
220 CvMat** count;
221 CvMat** sum;
222 CvMat** productsum;
223 CvMat** avg;
224 CvMat** inv_eigen_values;
225 CvMat** cov_rotate_mats;
226 CvMat* c;
242 CvKNearest( const CvMat* trainData, const CvMat* responses,
243 const CvMat* sampleIdx=0, bool isRegression=false, int max_k=32 );
245 virtual bool train( const CvMat* trainData, const CvMat* responses,
246 const CvMat* sampleIdx=0, bool is_regression=false,
249 virtual float find_nearest( const CvMat* samples, int k, CV_OUT CvMat* results=0,
250 const float** neighbors=0, CV_OUT CvMat* neighborResponses=0, CV_OUT CvMat* dist=0 ) const;
272 const float* neighbor_responses, const float* dist, CvMat* _results,
273 CvMat* _neighbor_responses, CvMat* _dist, Cv32suf* sort_buf ) const;
275 virtual void find_neighbors_direct( const CvMat* _samples, int k, int start, int end,
297 CvMat* class_weights, CvTermCriteria term_crit );
308 CvMat* class_weights; // for CV_SVM_C_SVC
472 CvSVM( const CvMat* trainData, const CvMat* responses,
473 const CvMat* varIdx=0, const CvMat* sampleIdx=0,
476 virtual bool train( const CvMat* trainData, const CvMat* responses,
477 const CvMat* varIdx=0, const CvMat* sampleIdx=0,
480 virtual bool train_auto( const CvMat* trainData, const CvMat* responses,
481 const CvMat* varIdx, const CvMat* sampleIdx, CvSVMParams params,
491 virtual float predict( const CvMat* sample, bool returnDFVal=false ) const;
492 virtual float predict( const CvMat* samples, CV_OUT CvMat* results, bool returnDFVal=false ) const;
535 const CvMat* responses, CvMemStorage* _storage, double* alpha );
547 CvMat* class_labels;
551 CvMat* var_idx;
552 CvMat* class_weights;
654 CvDTreeTrainData( const CvMat* trainData, int tflag,
655 const CvMat* responses, const CvMat* varIdx=0,
656 const CvMat* sampleIdx=0, const CvMat* varType=0,
657 const CvMat* missingDataMask=0,
662 virtual void set_data( const CvMat* trainData, int tflag,
663 const CvMat* responses, const CvMat* varIdx=0,
664 const CvMat* sampleIdx=0, const CvMat* varType=0,
665 const CvMat* missingDataMask=0,
671 virtual void get_vectors( const CvMat* _subsample_idx,
674 virtual CvDTreeNode* subsample_data( const CvMat* _subsample_idx );
714 const CvMat* train_data;
715 const CvMat* responses;
716 CvMat* responses_copy; // used in Boosting
722 CvMat* cat_count;
723 CvMat* cat_ofs;
724 CvMat* cat_map;
726 CvMat* counts;
727 CvMat* buf;
734 CvMat* direction;
735 CvMat* split_buf;
737 CvMat* var_idx;
738 CvMat* var_type; // i-th element =
741 CvMat* priors;
742 CvMat* priors_mult;
774 virtual bool train( const CvMat* trainData, int tflag,
775 const CvMat* responses, const CvMat* varIdx=0,
776 const CvMat* sampleIdx=0, const CvMat* varType=0,
777 const CvMat* missingDataMask=0,
785 virtual bool train( CvDTreeTrainData* trainData, const CvMat* subsampleIdx );
787 virtual CvDTreeNode* predict( const CvMat* sample, const CvMat* missingDataMask=0,
800 virtual const CvMat* get_var_importance();
818 virtual bool do_train( const CvMat* _subsample_idx );
854 CvMat* var_importance;
856 CvMat train_data_hdr, responses_hdr;
876 virtual bool train( CvDTreeTrainData* trainData, const CvMat* _subsample_idx, CvRTrees* forest );
882 virtual bool train( const CvMat* trainData, int tflag,
883 const CvMatCvMat* varIdx=0,
884 const CvMat* sampleIdx=0, const CvMat* varType=0,
885 const CvMat* missingDataMask=0,
888 virtual bool train( CvDTreeTrainData* trainData, const CvMat* _subsample_idx );
923 virtual bool train( const CvMat* trainData, int tflag,
924 const CvMat* responses, const CvMat* varIdx=0,
925 const CvMat* sampleIdx=0, const CvMat* varType=0,
926 const CvMat* missingDataMask=0,
930 virtual float predict( const CvMat* sample, const CvMat* missing = 0 ) const;
931 virtual float predict_prob( const CvMat* sample, const CvMat* missing = 0 ) const;
944 virtual const CvMat* get_var_importance();
945 virtual float get_proximity( const CvMat* sample1, const CvMat* sample2,
946 const CvMat* missing1 = 0, const CvMat* missing2 = 0 ) const;
955 CvMat* get_active_var_mask();
969 CvMat train_data_hdr, responses_hdr;
974 CvMat* var_importance;
978 CvMat* active_var_mask;
986 virtual void set_data( const CvMat* trainData, int tflag,
987 const CvMat* responses, const CvMat* varIdx=0,
988 const CvMat* sampleIdx=0, const CvMat* varType=0,
989 const CvMat* missingDataMask=0,
998 virtual void get_vectors( const CvMat* _subsample_idx, float* values, uchar* missing,
1000 virtual CvDTreeNode* subsample_data( const CvMat* _subsample_idx );
1001 const CvMat* missing_mask;
1024 virtual bool train( const CvMat* trainData, int tflag,
1025 const CvMat* responses, const CvMat* varIdx=0,
1026 const CvMat* sampleIdx=0, const CvMat* varType=0,
1027 const CvMat* missingDataMask=0,
1067 const CvMat* subsample_idx, CvBoost* ensemble );
1075 virtual bool train( const CvMat* trainData, int tflag,
1076 const CvMat* responses, const CvMat* varIdx=0,
1077 const CvMat* sampleIdx=0, const CvMat* varType=0,
1078 const CvMat* missingDataMask=0,
1080 virtual bool train( CvDTreeTrainData* trainData, const CvMat* _subsample_idx );
1119 CvBoost( const CvMat* trainData, int tflag,
1120 const CvMat* responses, const CvMat* varIdx=0,
1121 const CvMat* sampleIdx=0, const CvMat* varType=0,
1122 const CvMat* missingDataMask=0,
1125 virtual bool train( const CvMat* trainData, int tflag,
1126 const CvMat* responses, const CvMat* varIdx=0,
1127 const CvMat* sampleIdx=0, const CvMat* varType=0,
1128 const CvMat* missingDataMask=0,
1136 virtual float predict( const CvMat* sample, const CvMat* missing=0,
1137 CvMat* weak_responses=0, CvSlice slice=CV_WHOLE_SEQ,
1165 virtual const CvMat* get_active_vars(bool absolute_idx=true);
1169 CvMat* get_weights();
1170 CvMat* get_subtree_weights();
1171 CvMat* get_weak_response();
1186 CvMat train_data_hdr, responses_hdr;
1191 CvMat* active_vars;
1192 CvMat* active_vars_abs;
1195 CvMat* orig_response;
1196 CvMat* sum_response;
1197 CvMat* weak_eval;
1198 CvMat* subsample_mask;
1199 CvMat* weights;
1200 CvMat* subtree_weights;
1335 // CvGBTrees( const CvMat* trainData, int tflag,
1336 const CvMat* responses, const CvMat* varIdx=0,
1337 const CvMat* sampleIdx=0, const CvMat* varType=0,
1338 const CvMat* missingDataMask=0,
1367 CvGBTrees( const CvMat* trainData, int tflag,
1368 const CvMat* responses, const CvMat* varIdx=0,
1369 const CvMat* sampleIdx=0, const CvMat* varType=0,
1370 const CvMat* missingDataMask=0,
1384 // virtual bool train( const CvMat* trainData, int tflag,
1385 const CvMat* responses, const CvMat* varIdx=0,
1386 const CvMat* sampleIdx=0, const CvMat* varType=0,
1387 const CvMat* missingDataMask=0,
1419 virtual bool train( const CvMat* trainData, int tflag,
1420 const CvMat* responses, const CvMat* varIdx=0,
1421 const CvMat* sampleIdx=0, const CvMat* varType=0,
1422 const CvMat* missingDataMask=0,
1452 // virtual float predict_serial( const CvMat* sample, const CvMat* missing=0,
1453 CvMat* weak_responses=0, CvSlice slice = CV_WHOLE_SEQ,
1475 virtual float predict_serial( const CvMat* sample, const CvMat* missing=0,
1476 CvMat* weakResponses=0, CvSlice slice = CV_WHOLE_SEQ,
1484 // virtual float predict( const CvMat* sample, const CvMat* missing=0,
1485 CvMat* weak_responses=0, CvSlice slice = CV_WHOLE_SEQ,
1507 virtual float predict( const CvMat* sample, const CvMat* missing=0,
1508 CvMat* weakResponses=0, CvSlice slice = CV_WHOLE_SEQ,
1643 // virtual float find_optimal_value( const CvMat* _Idx );
1651 virtual float find_optimal_value( const CvMat* _Idx );
1754 int get_len(const CvMat* mat) const;
1761 CvMat* orig_response;
1762 CvMat* sum_response;
1763 CvMat* sum_response_tmp;
1764 CvMat* sample_idx;
1765 CvMat* subsample_train;
1766 CvMat* subsample_test;
1767 CvMat* missing;
1768 CvMat* class_labels;
1810 CvANN_MLP( const CvMat* layerSizes,
1816 virtual void create( const CvMat* layerSizes,
1820 virtual int train( const CvMat* inputs, const CvMat* outputs,
1821 const CvMat* sampleWeights, const CvMat* sampleIdx=0,
1824 virtual float predict( const CvMat* inputs, CV_OUT CvMat* outputs ) const;
1853 const CvMat* get_layer_sizes() { return layer_sizes; }
1860 virtual void calc_activ_func_deriv( CvMat* xf, CvMat* deriv, const double* bias ) const;
1864 virtual bool prepare_to_train( const CvMat* _inputs, const CvMat* _outputs,
1865 const CvMat* _sample_weights, const CvMat* sampleIdx,
1874 virtual void calc_activ_func( CvMat* xf, const double* bias ) const;
1878 virtual void scale_input( const CvMat* _src, CvMat* _dst ) const;
1879 virtual void scale_output( const CvMat* _src, CvMat* _dst ) const;
1886 CvMat* layer_sizes;
1887 CvMat* wbuf;
1888 CvMat* sample_weights;
1904 CVAPI(void) cvRandMVNormal( CvMat* mean, CvMat* cov, CvMat* sample,
1908 CVAPI(void) cvRandGaussMixture( CvMat* means[],
1909 CvMat* covs[],
1912 CvMat* sample,
1913 CvMat* sampClasses CV_DEFAULT(0) );
1918 CVAPI(void) cvCreateTestSet( int type, CvMat** samples,
1921 CvMat** responses,
1958 const CvMat* get_values() const;
1959 const CvMat* get_responses();
1960 const CvMat* get_missing() const;
1970 const CvMat* get_train_sample_idx() const;
1971 const CvMat* get_test_sample_idx() const;
1974 const CvMat* get_var_idx();
1979 const CvMat* get_var_types();
2007 CvMat* values;
2008 CvMat* missing;
2009 CvMat* var_types;
2010 CvMat* var_idx_mask;
2012 CvMat* response_out; // header
2013 CvMat* var_idx_out; // mat
2014 CvMat* var_types_out; // mat
2026 CvMat* train_sample_idx;
2027 CvMat* test_sample_idx;
