152     Mat getResponses() const { return responses; }  in getResponses()
177         return getSubVector(responses, getTrainSampleIdx());  in getTrainResponses()
186         return idx.empty() ? Mat() : getSubVector(responses, idx);  in getTestResponses()
216         responses.release();  in clear()
240         responses = _responses.getMat();  in setData()
282         if( !responses.empty() )  in setData()
284             CV_Assert( responses.type() == CV_32F || responses.type() == CV_32S );  in setData()
285             if( (responses.cols == 1 || responses.rows == 1) && (int)responses.total() == nsamples )  in setData()
289                 CV_Assert( (layout == ROW_SAMPLE && responses.rows == nsamples) ||  in setData()
290                            (layout == COL_SAMPLE && responses.cols == nsamples) );  in setData()
291                 noutputvars = layout == ROW_SAMPLE ? responses.cols : responses.rows;  in setData()
293             if( !responses.isContinuous() || (layout == COL_SAMPLE && noutputvars > 1) )  in setData()
296                 transpose(responses, temp);  in setData()
297                 responses = temp;  in setData()
313 …varType.at<uchar>(ninputvars) = (uchar)(responses.type() < CV_32F ? VAR_CATEGORICAL : VAR_ORDERED);  in setData()
400             preprocessCategorical(responses, &normCatResponses, labels, &counters, sortbuf);  in setData()
966     Mat samples, missing, varType, varIdx, responses, missingSubst;  member in cv::ml::TrainDataImpl
986 Ptr<TrainData> TrainData::create(InputArray samples, int layout, InputArray responses,  in create()  argument
991     td->setData(samples, layout, responses, varIdx, sampleIdx, sampleWeights, varType, noArray());  in create()