| /dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/ensemble/_hist_gradient_boosting/ |
| H A D | binning.py | 156 is_categorical=None, argument
163 self.is_categorical = is_categorical
201 if self.is_categorical is None:
204 self.is_categorical_ = np.asarray(self.is_categorical, dtype=np.uint8)
213 is_categorical = self.is_categorical_[f_idx]
215 if is_categorical and known_cats is None:
219 if not is_categorical and known_cats is not None:
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| H A D | grower.py | 199 is_categorical=None, argument
255 if is_categorical is None:
256 is_categorical = np.zeros(shape=X_binned.shape[1], dtype=np.uint8)
258 is_categorical = np.asarray(is_categorical, dtype=np.uint8)
262 is_categorical == 1, monotonic_cst != MonotonicConstraint.NO_CST
277 is_categorical,
291 self.is_categorical = is_categorical
491 self.n_categorical_splits += node.split_info.is_categorical
665 node["is_categorical"] = split_info.is_categorical
672 elif split_info.is_categorical:
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| H A D | splitting.pyx | 47 unsigned char is_categorical
86 is_categorical : bool
113 self.is_categorical = is_categorical
195 self.is_categorical = is_categorical
300 unsigned char is_categorical = split_info.is_categorical
325 if is_categorical:
464 const unsigned char [::1] is_categorical = self.is_categorical
483 split_infos[feature_idx].is_categorical = is_categorical[feature_idx]
540 if split_info.is_categorical:
1082 unsigned char is_categorical,
[all …]
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| H A D | common.pxd | 36 unsigned char is_categorical
38 # Only used if is_categorical is True
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| H A D | common.pyx | 31 ('is_categorical', np.uint8),
33 # Only used if is_categorical is True
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| H A D | gradient_boosting.py | 161 is_categorical = np.zeros(n_features, dtype=bool)
162 is_categorical[categorical_features] = True
170 is_categorical = categorical_features
172 if not np.any(is_categorical):
181 if is_categorical[f_idx]:
204 return is_categorical, known_categories
336 is_categorical=self.is_categorical_,
517 is_categorical=self.is_categorical_,
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| H A D | _predictor.pyx | 68 elif node.is_categorical:
134 elif node.is_categorical:
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| /dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/ensemble/_hist_gradient_boosting/tests/ |
| H A D | test_splitting.py | 67 is_categorical,
138 is_categorical = np.zeros_like(monotonic_cst, dtype=np.uint8)
145 is_categorical,
281 is_categorical = np.zeros_like(monotonic_cst, dtype=np.uint8)
288 is_categorical,
357 is_categorical = np.zeros_like(monotonic_cst, dtype=np.uint8)
364 is_categorical,
533 is_categorical,
638 is_categorical,
823 is_categorical,
[all …]
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| H A D | test_binning.py | 350 is_categorical=np.array([True]),
378 is_categorical=np.array([False, True]),
411 is_categorical=np.array([False, True, True]),
452 def test_categorical_parameters(is_categorical, known_categories, match): argument
458 is_categorical=is_categorical, known_categories=known_categories
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| H A D | test_grower.py | 451 is_categorical = np.ones(1, dtype=np.uint8)
460 is_categorical=is_categorical,
544 X_binned, gradients, hessians, is_categorical=[True], **grower_params
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| H A D | test_monotonic_contraints.py | 308 is_categorical = np.zeros_like(monotonic_cst, dtype=np.uint8)
318 is_categorical,
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| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/base/ |
| H A D | test_misc.py | 72 is_categorical = is_categorical_dtype(obj.dtype) or (
82 elif is_object or is_categorical:
|
| /dports/biology/avida/avida-2.12.4-src/apps/viewer-macos/src/viewer-core/ |
| H A D | MapScaleView.h | 38 bool is_categorical; variable
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| H A D | MapScaleView.mm | 100 if (is_categorical) {
163 is_categorical = state->GetColorScale().IsCategorical();
|
| /dports/math/py-pandas/pandas-1.2.5/pandas/core/dtypes/ |
| H A D | api.py | 7 is_categorical,
|
| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/dtypes/ |
| H A D | test_common.py | 203 assert com.is_categorical(cat)
204 assert com.is_categorical(pd.Series(cat))
205 assert com.is_categorical(pd.CategoricalIndex([1, 2, 3]))
207 assert not com.is_categorical([1, 2, 3])
213 com.is_categorical([1, 2, 3])
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| H A D | test_dtypes.py | 10 is_categorical,
168 assert is_categorical(s.dtype)
169 assert is_categorical(s)
170 assert not is_categorical(np.dtype("float64"))
171 assert not is_categorical(1.0)
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| /dports/misc/py-xgboost/xgboost-1.5.1/tests/cpp/tree/gpu_hist/ |
| H A D | test_evaluate_splits.cu | 18 void TestEvaluateSingleSplit(bool is_categorical) { in TestEvaluateSingleSplit() argument
41 if (is_categorical) { in TestEvaluateSingleSplit()
|
| /dports/misc/xgboost/xgboost-1.5.1/tests/cpp/tree/gpu_hist/ |
| H A D | test_evaluate_splits.cu | 18 void TestEvaluateSingleSplit(bool is_categorical) { in TestEvaluateSingleSplit() argument
41 if (is_categorical) { in TestEvaluateSingleSplit()
|
| /dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/NOMAD/src/ |
| H A D | Directions.hpp | 230 bool is_categorical ( void ) const in is_categorical() function in NOMAD::Directions
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| H A D | Variable_Group.cpp | 190 if ( _directions->is_categorical() ) in display()
|
| /dports/math/py-pandas/pandas-1.2.5/doc/source/reference/ |
| H A D | general_utility_functions.rst | 108 api.types.is_categorical
|
| /dports/biology/plink/plink-ng-79b2df8c/2.0/ |
| H A D | plink2_psam.cc | 622 const uint32_t is_categorical = IsSet(categorical_phenos, pheno_idx); in LoadPsam() local
628 if (!is_categorical) { in LoadPsam()
653 if (is_categorical) { in LoadPsam()
1336 const uint32_t is_categorical = IsSet(categorical_phenos, new_pheno_idx); in LoadPhenos() local
1342 if (!is_categorical) { in LoadPhenos()
1367 if (is_categorical) { in LoadPhenos()
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| /dports/misc/py-xgboost/xgboost-1.5.1/src/tree/ |
| H A D | tree_model.cc | 96 auto is_categorical = tree.GetSplitTypes()[nid] == FeatureType::kCategorical; in SplitNode() local
99 CHECK(is_categorical) in SplitNode()
104 auto is_numerical = !is_categorical; in SplitNode()
136 if (is_categorical) { in SplitNode()
618 template <bool is_categorical>
625 if (is_categorical) { in BuildEdge()
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| /dports/misc/xgboost/xgboost-1.5.1/src/tree/ |
| H A D | tree_model.cc | 96 auto is_categorical = tree.GetSplitTypes()[nid] == FeatureType::kCategorical; in SplitNode() local
99 CHECK(is_categorical) in SplitNode()
104 auto is_numerical = !is_categorical; in SplitNode()
136 if (is_categorical) { in SplitNode()
618 template <bool is_categorical>
625 if (is_categorical) { in BuildEdge()
|