| /dports/graphics/tesseract/tesseract-5.0.0/src/classify/ |
| H A D | trainingsample.cpp | 64 if (fwrite(&num_features_, sizeof(num_features_), 1, fp) != 1) { in Serialize()
73 if (fwrite(features_, sizeof(*features_), num_features_, fp) != num_features_) { in Serialize()
115 if (fread(&num_features_, sizeof(num_features_), 1, fp) != 1) { in DeSerialize()
126 ReverseN(&num_features_, sizeof(num_features_)); in DeSerialize()
131 if (num_features_ > UINT16_MAX) { in DeSerialize()
139 if (fread(features_, sizeof(*features_), num_features_, fp) != num_features_) { in DeSerialize()
163 sample->num_features_ = num_features; in CopyFromFeatures()
219 sample->num_features_ = num_features_; in Copy()
220 if (num_features_ > 0) { in Copy()
243 num_features_ = 0; in ExtractCharDesc()
[all …]
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| H A D | trainingsample.h | 60 , num_features_(0) in TrainingSample()
144 return num_features_; in num_features()
212 uint32_t num_features_; variable
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| H A D | intmatcher.cpp | 152 num_features_ = 0; in ClassPruner()
167 num_features_ = num_features; in ComputeScores()
237 if (num_features_ < expected_num_features[class_id]) { in AdjustForExpectedNumFeatures()
238 int deficit = expected_num_features[class_id] - num_features_; in AdjustForExpectedNumFeatures()
240 class_count_[class_id] * deficit / (num_features_ * cutoff_strength + deficit); in AdjustForExpectedNumFeatures()
328 for (int f = 0; f < num_features_; ++f) { in DebugMatch()
360 tprintf("CP:%d classes, %d features:\n", num_classes_, num_features_); in SummarizeResult()
368 100.0 - 100.0 * sort_key_[num_classes_ - i] / (CLASS_PRUNER_CLASS_MASK * num_features_)); in SummarizeResult()
381 (static_cast<float>(CLASS_PRUNER_CLASS_MASK) * num_features_); in SetupResults()
404 int num_features_; member in tesseract::ClassPruner
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| /dports/misc/py-xgboost/xgboost-1.5.1/src/data/ |
| H A D | adapter.h | 203 num_features_(num_features) {} in DenseAdapterBatch()
225 return Line(values_ + idx * num_features_, num_features_, idx); in GetLine()
232 size_t num_features_; variable
415 num_features_(num_features) {} in CSCAdapterBatch()
437 size_t Size() const { return num_features_; } in Size()
450 size_t num_features_; variable
480 num_features_(num_features), in DataTableAdapterBatch()
573 size_t Size() const { return num_features_; } in Size()
582 size_t num_features_; variable
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| /dports/misc/xgboost/xgboost-1.5.1/src/data/ |
| H A D | adapter.h | 203 num_features_(num_features) {} in DenseAdapterBatch()
225 return Line(values_ + idx * num_features_, num_features_, idx); in GetLine()
232 size_t num_features_; variable
415 num_features_(num_features) {} in CSCAdapterBatch()
437 size_t Size() const { return num_features_; } in Size()
450 size_t num_features_; variable
480 num_features_(num_features), in DataTableAdapterBatch()
573 size_t Size() const { return num_features_; } in Size()
582 size_t num_features_; variable
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| /dports/misc/py-xgboost/xgboost-1.5.1/src/tree/gpu_hist/ |
| H A D | feature_groups.cuh | 23 __host__ __device__ FeatureGroup(int start_feature_, int num_features_, in FeatureGroup()
25 start_feature(start_feature_), num_features(num_features_), in FeatureGroup()
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| /dports/misc/xgboost/xgboost-1.5.1/src/tree/gpu_hist/ |
| H A D | feature_groups.cuh | 23 __host__ __device__ FeatureGroup(int start_feature_, int num_features_, in FeatureGroup()
25 start_feature(start_feature_), num_features(num_features_), in FeatureGroup()
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| /dports/graphics/vigra/vigra-8acd73a/include/vigra/random_forest_3/ |
| H A D | random_forest.hxx | 162 return problem_spec_.num_features_; in num_features()
255 vigra_precondition((size_t)features.shape()[1] == problem_spec_.num_features_, in predict()
282 vigra_precondition((size_t)features.shape()[1] == problem_spec_.num_features_, in predict_probabilities()
361 vigra_precondition((size_t)features.shape()[1] == problem_spec_.num_features_, in leaf_ids()
412 vigra_precondition(features.shape()[1] == problem_spec_.num_features_, in leaf_ids_impl()
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| H A D | random_forest_common.hxx | 810 num_features_(0), in ProblemSpec()
820 num_features_ = n; in num_features()
858 COMPARE(num_features_); in operator ==()
868 size_t num_features_; member in vigra::rf3::ProblemSpec
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| /dports/graphics/vigra/vigra-8acd73a/include/vigra/ |
| H A D | random_forest_3_hdf5_impex.hxx | 311 h5context.write("column_count_", p.num_features_); in random_forest_export_HDF5()
349 topology.push_back(p.num_features_); in random_forest_export_HDF5()
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| H A D | random_forest_3.hxx | 176 vigra_precondition(num_features == spec.num_features_, in random_forest_single_tree()
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