prepare_train_data  186 samples/cpp/letter_recog.cpp         Ptr<TrainData> tdata = prepare_train_data(data, responses, ntrain_samples);
prepare_train_data  439 samples/cpp/letter_recog.cpp     Ptr<TrainData> tdata = prepare_train_data(data, responses, ntrain_samples);
prepare_train_data  466 samples/cpp/letter_recog.cpp     Ptr<TrainData> tdata = prepare_train_data(data, responses, ntrain_samples);
prepare_train_data  503 samples/cpp/letter_recog.cpp         Ptr<TrainData> tdata = prepare_train_data(data, responses, ntrain_samples);
prepare_train_data  105 samples/cpp/points_classifier.cpp     Ptr<NormalBayesClassifier> normalBayesClassifier = StatModel::train<NormalBayesClassifier>(prepare_train_data());
prepare_train_data  119 samples/cpp/points_classifier.cpp     knn->train(prepare_train_data());
prepare_train_data  137 samples/cpp/points_classifier.cpp     svm->train(prepare_train_data());
prepare_train_data  159 samples/cpp/points_classifier.cpp     dtree->train(prepare_train_data());
prepare_train_data  174 samples/cpp/points_classifier.cpp     boost->train(prepare_train_data());
prepare_train_data  191 samples/cpp/points_classifier.cpp     Ptr<GBTrees> gbtrees = StatModel::train<GBTrees>(prepare_train_data(), params);
prepare_train_data  209 samples/cpp/points_classifier.cpp     rtrees->train(prepare_train_data());