| /external/opencv/ml/src/ |
| D | mlboost.cpp | 1057 CvMat _sample, _mask; in update_weights() local
1064 _sample = cvMat( 1, data->var_count, CV_32F ); in update_weights()
1071 _sample.data.fl = values; in update_weights()
1073 values += _sample.cols; in update_weights()
1075 weak_eval->data.db[i] = tree->predict( &_sample, &_mask, true )->value; in update_weights()
1262 CvBoost::predict( const CvMat* _sample, const CvMat* _missing, in predict() argument
1287 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || in predict()
1288 _sample->cols != 1 && _sample->rows != 1 || in predict()
1289 _sample->cols + _sample->rows - 1 != data->var_all && !raw_mode || in predict()
1290 _sample->cols + _sample->rows - 1 != data->var_count && raw_mode ) in predict()
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| D | mlem.cpp | 209 CvEM::predict( const CvMat* _sample, CvMat* _probs ) const in predict() argument
229 CV_CALL( cvPreparePredictData( _sample, dims, 0, params.nclusters, _probs, &sample_data )); in predict()
293 if( sample_data != _sample->data.fl ) in predict()
982 CvMat* cov = covs[k], _mean, _sample; in run_em() local
987 cvGetRow( samples, &_sample, k ); in run_em()
1002 _sample.data.db = (double*)(samples->data.ptr + samples->step*i); in run_em()
1006 cvMulTransposed( &_sample, covs_item, 1, &_mean ); in run_em()
1012 double val = _sample.data.db[j] - _mean.data.db[j]; in run_em()
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| D | mltree.cpp | 2881 CvDTreeNode* CvDTree::predict( const CvMat* _sample, in predict() argument
2903 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || in predict()
2904 _sample->cols != 1 && _sample->rows != 1 || in predict()
2905 _sample->cols + _sample->rows - 1 != data->var_all && !preprocessed_input || in predict()
2906 _sample->cols + _sample->rows - 1 != data->var_count && preprocessed_input ) in predict()
2911 sample = _sample->data.fl; in predict()
2912 step = CV_IS_MAT_CONT(_sample->type) ? 1 : _sample->step/sizeof(sample[0]); in predict()
2925 !CV_ARE_SIZES_EQ(_missing, _sample) ) in predict()
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| D | ml_inner_functions.cpp | 1148 cvPreparePredictData( const CvArr* _sample, int dims_all, in cvPreparePredictData() argument
1160 const CvMat* sample = (const CvMat*)_sample; in cvPreparePredictData()
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| /external/opencv3/apps/traincascade/ |
| D | old_ml_boost.cpp | 1271 CvMat _sample, _mask; in update_weights() local
1277 _sample = cvMat( 1, data->var_count, CV_32F ); in update_weights()
1284 _sample.data.fl = values; in update_weights()
1286 values += _sample.cols; in update_weights()
1288 weak_eval->data.db[i] = tree->predict( &_sample, &_mask, true )->value; in update_weights()
1603 CvBoost::predict( const CvMat* _sample, const CvMat* _missing, in predict() argument
1617 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || in predict()
1618 (_sample->cols != 1 && _sample->rows != 1) || in predict()
1619 (_sample->cols + _sample->rows - 1 != data->var_all && !raw_mode) || in predict()
1620 (active_vars && _sample->cols + _sample->rows - 1 != active_vars->cols && raw_mode) ) in predict()
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| D | old_ml_tree.cpp | 3618 CvDTreeNode* CvDTree::predict( const CvMat* _sample, in predict() argument
3630 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || in predict()
3631 (_sample->cols != 1 && _sample->rows != 1) || in predict()
3632 (_sample->cols + _sample->rows - 1 != data->var_all && !preprocessed_input) || in predict()
3633 (_sample->cols + _sample->rows - 1 != data->var_count && preprocessed_input) ) in predict()
3638 const float* sample = _sample->data.fl; in predict()
3639 int step = CV_IS_MAT_CONT(_sample->type) ? 1 : _sample->step/sizeof(sample[0]); in predict()
3652 !CV_ARE_SIZES_EQ(_missing, _sample) ) in predict()
3735 CvDTreeNode* CvDTree::predict( const Mat& _sample, const Mat& _missing, bool preprocessed_input ) c… in predict() argument
3737 CvMat sample = _sample, mmask = _missing; in predict()
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| D | old_ml_inner_functions.cpp | 1078 cvPreparePredictData( const CvArr* _sample, int dims_all, in cvPreparePredictData() argument
1090 const CvMat* sample = (const CvMat*)_sample; in cvPreparePredictData()
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| /external/libweave/examples/daemon/sample/ |
| D | sample.cc | 16 "_sample": {
67 kComponent, R"({"_sample": {"pingCount": 0}})", nullptr)); in Register()
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| /external/opencv3/modules/ml/src/ |
| D | gbt.cpp | 806 float CvGBTrees::predict_serial( const CvMat* _sample, const CvMat* _missing,
841 float p = (float)(tree->predict(_sample, _missing)->value);
905 const CvMat* _sample, const CvMat* _missing, float* _sum ) :
906 weak(_weak), sum(_sum), k(_k), sample(_sample),
955 float CvGBTrees::predict( const CvMat* _sample, const CvMat* _missing,
968 params.shrinkage, _sample, _missing, sum);
1360 CvMat _sample = sample, miss = _missing;
1361 return predict(&_sample, _missing.empty() ? 0 : &miss, 0,
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| D | em.cpp | 188 Vec2d predict2(InputArray _sample, OutputArray _probs) const in predict2() argument
191 Mat sample = _sample.getMat(); in predict2()
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| /external/libweave/examples/daemon/ |
| D | README.md | 106 "name": "_sample.hello",
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| /external/opencv/ml/include/ |
| D | ml.h | 514 virtual float predict( const CvMat* _sample ) const;
845 virtual CvDTreeNode* predict( const CvMat* _sample, const CvMat* _missing_data_mask=0,
1101 virtual float predict( const CvMat* _sample, const CvMat* _missing=0,
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