NTRAINING_SAMPLES   34 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     Mat trainData(2*NTRAINING_SAMPLES, 2, CV_32FC1);
NTRAINING_SAMPLES   35 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     Mat labels   (2*NTRAINING_SAMPLES, 1, CV_32SC1);
NTRAINING_SAMPLES   40 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     int nLinearSamples = (int) (FRAC_LINEAR_SEP * NTRAINING_SAMPLES);
NTRAINING_SAMPLES   53 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     trainClass = trainData.rowRange(2*NTRAINING_SAMPLES-nLinearSamples, 2*NTRAINING_SAMPLES);
NTRAINING_SAMPLES   65 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     trainClass = trainData.rowRange(  nLinearSamples, 2*NTRAINING_SAMPLES-nLinearSamples);
NTRAINING_SAMPLES   74 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     labels.rowRange(                0,   NTRAINING_SAMPLES).setTo(1);  // Class 1
NTRAINING_SAMPLES   75 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     labels.rowRange(NTRAINING_SAMPLES, 2*NTRAINING_SAMPLES).setTo(2);  // Class 2
NTRAINING_SAMPLES  112 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     for (int i = 0; i < NTRAINING_SAMPLES; ++i)
NTRAINING_SAMPLES  119 samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp     for (int i = NTRAINING_SAMPLES; i <2*NTRAINING_SAMPLES; ++i)