Searched refs:tparams_node (Results 1 - 2 of 2) sorted by relevance
/external/opencv/ml/src/ |
H A D | mlann_mlp.cpp | 1407 CvFileNode* tparams_node; local 1426 tparams_node = cvGetFileNodeByName( fs, node, "training_params" ); 1429 if( tparams_node ) 1431 const char* tmethod_name = cvReadStringByName( fs, tparams_node, "train_method", "" ); 1437 params.bp_dw_scale = cvReadRealByName( fs, tparams_node, "dw_scale", 0 ); 1438 params.bp_moment_scale = cvReadRealByName( fs, tparams_node, "moment_scale", 0 ); 1443 params.rp_dw0 = cvReadRealByName( fs, tparams_node, "dw0", 0 ); 1444 params.rp_dw_plus = cvReadRealByName( fs, tparams_node, "dw_plus", 0 ); 1445 params.rp_dw_minus = cvReadRealByName( fs, tparams_node, "dw_minus", 0 ); 1446 params.rp_dw_min = cvReadRealByName( fs, tparams_node, "dw_mi [all...] |
H A D | mltree.cpp | 1070 CvFileNode *tparams_node, *vartype_node; local 1080 tparams_node = cvGetFileNodeByName( fs, node, "training_params" ); 1082 if( tparams_node ) // training parameters are not necessary 1084 params.use_surrogates = cvReadIntByName( fs, tparams_node, "use_surrogates", 1 ) != 0; 1088 params.max_categories = cvReadIntByName( fs, tparams_node, "max_categories" ); 1093 (float)cvReadRealByName( fs, tparams_node, "regression_accuracy" ); 1096 params.max_depth = cvReadIntByName( fs, tparams_node, "max_depth" ); 1097 params.min_sample_count = cvReadIntByName( fs, tparams_node, "min_sample_count" ); 1098 params.cv_folds = cvReadIntByName( fs, tparams_node, "cross_validation_folds" ); 1102 params.use_1se_rule = cvReadIntByName( fs, tparams_node, "use_1se_rul [all...] |
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