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322,500 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_factor_analysis.py | sklearn.decomposition._factor_analysis.FactorAnalysis | from ..utils.extmath import _randomized_svd, fast_logdet, squared_norm
import warnings
from numbers import Integral, Real
from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from ..exceptions import ConvergenceWarning
from ..utils.validation import check_is_fitted, validate... |
class FactorAnalysis(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator):
'''Factor Analysis (FA).
A simple linear generative model with Gaussian latent variables.
The observations are assumed to be caused by a linear transformation of
lower dimensional latent factors and added Gaussian n... | 14 | 9 | 24 | 3 | 14 | 7 | 2 | 1.08 | 3 | 3 | 1 | 0 | 9 | 14 | 9 | 45 | 397 | 75 | 156 | 71 | 130 | 168 | 108 | 57 | 96 | 8 | 2 | 2 | 20 |
322,501 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_fastica.py | sklearn.decomposition._fastica.FastICA | from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from ..utils import as_float_array, check_array, check_random_state
from ..utils._param_validation import Interval, Options, StrOptions, validate_params
import warnings
from scipy import linalg
import numpy as np
from numb... |
class FastICA(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator):
'''FastICA: a fast algorithm for Independent Component Analysis.
The implementation is based on [1]_.
Read more in the :ref:`User Guide <ICA>`.
Parameters
----------
n_components : int, default=None
Number ... | 13 | 7 | 31 | 4 | 18 | 9 | 4 | 1.02 | 3 | 3 | 0 | 0 | 8 | 16 | 8 | 44 | 438 | 76 | 181 | 62 | 155 | 184 | 112 | 46 | 102 | 23 | 2 | 3 | 33 |
322,502 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_incremental_pca.py | sklearn.decomposition._incremental_pca.IncrementalPCA | from ..base import _fit_context
from ..utils import gen_batches
from scipy import linalg, sparse
from ..utils._param_validation import Interval
from sklearn.utils import metadata_routing
from ..utils.validation import validate_data
from ._base import _BasePCA
from numbers import Integral
from ..utils.extmath import _in... |
class IncrementalPCA(_BasePCA):
'''Incremental principal components analysis (IPCA).
Linear dimensionality reduction using Singular Value Decomposition of
the data, keeping only the most significant singular vectors to
project the data to a lower dimensional space. The input data is centered
but no... | 8 | 4 | 45 | 5 | 28 | 12 | 4 | 1.28 | 1 | 3 | 0 | 0 | 5 | 14 | 5 | 68 | 406 | 64 | 150 | 39 | 142 | 192 | 85 | 37 | 79 | 12 | 4 | 2 | 21 |
322,503 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_kernel_pca.py | sklearn.decomposition._kernel_pca.KernelPCA | from ..utils.validation import _check_psd_eigenvalues, check_is_fitted, validate_data
from ..utils.extmath import _randomized_eigsh, svd_flip
from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from ..exceptions import NotFittedError
import numpy as np
from ..utils._param_v... |
class KernelPCA(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator):
'''Kernel Principal component analysis (KPCA).
Non-linear dimensionality reduction through the use of kernels [1]_, see also
:ref:`metrics`.
It uses the :func:`scipy.linalg.eigh` LAPACK implementation of the full SVD
... | 13 | 7 | 29 | 4 | 14 | 11 | 2 | 1.58 | 3 | 5 | 2 | 0 | 10 | 23 | 10 | 46 | 546 | 90 | 177 | 71 | 145 | 280 | 96 | 50 | 85 | 8 | 2 | 2 | 24 |
322,504 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_lda.py | sklearn.decomposition._lda.LatentDirichletAllocation | from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from ..utils.validation import check_is_fitted, check_non_negative, validate_data
from ..utils import check_random_state, gen_batches, gen_even_slices
import numpy as np
from ._online_lda_fast import _dirichlet_expectation... |
class LatentDirichletAllocation(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator):
'''Latent Dirichlet Allocation with online variational Bayes algorithm.
The implementation is based on [1]_ and [2]_.
.. versionadded:: 0.17
Read more in the :ref:`User Guide <LatentDirichletAllocation>`.... | 21 | 15 | 34 | 5 | 17 | 12 | 3 | 1.09 | 3 | 6 | 1 | 0 | 16 | 24 | 16 | 52 | 796 | 149 | 309 | 126 | 267 | 338 | 185 | 100 | 167 | 8 | 2 | 4 | 44 |
322,505 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_nmf.py | sklearn.decomposition._nmf.MiniBatchNMF | from scipy import linalg
from ..utils import check_array, check_random_state, gen_batches
from ..utils.validation import check_is_fitted, check_non_negative, validate_data
from .._config import config_context
from numbers import Integral, Real
from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, Transform... |
class MiniBatchNMF(_BaseNMF):
'''Mini-Batch Non-Negative Matrix Factorization (NMF).
.. versionadded:: 1.1
Find two non-negative matrices, i.e. matrices with all non-negative elements,
(`W`, `H`) whose product approximates the non-negative matrix `X`. This
factorization can be used for example for ... | 12 | 8 | 47 | 8 | 26 | 13 | 4 | 1.09 | 1 | 8 | 1 | 0 | 9 | 22 | 9 | 73 | 644 | 135 | 243 | 78 | 210 | 266 | 133 | 52 | 123 | 10 | 5 | 2 | 33 |
322,506 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_nmf.py | sklearn.decomposition._nmf.NMF | from ..utils.validation import check_is_fitted, check_non_negative, validate_data
from .._config import config_context
from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from ..utils._param_validation import Interval, StrOptions, validate_params
import numpy as np
from ..e... |
class NMF(_BaseNMF):
'''Non-Negative Matrix Factorization (NMF).
Find two non-negative matrices, i.e. matrices with all non-negative elements, (W, H)
whose product approximates the non-negative matrix X. This factorization can be used
for example for dimensionality reduction, source separation or topic... | 7 | 4 | 44 | 6 | 25 | 13 | 2 | 1.65 | 1 | 4 | 1 | 0 | 5 | 10 | 5 | 69 | 439 | 92 | 131 | 37 | 109 | 216 | 41 | 17 | 35 | 5 | 5 | 1 | 11 |
322,507 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_nmf.py | sklearn.decomposition._nmf._BaseNMF | from abc import ABC
import numpy as np
import warnings
from ..utils._param_validation import Interval, StrOptions, validate_params
from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from numbers import Integral, Real
from ..utils.validation import check_is_fitted, check_no... |
class _BaseNMF(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator, ABC):
'''Base class for NMF and MiniBatchNMF.'''
def __init__(self, n_components='auto', *, init=None, beta_loss='frobenius', tol=0.0001, max_iter=200, random_state=None, alpha_W=0.0, alpha_H='same', l1_ratio=0.0, verbose=0):
... | 10 | 6 | 19 | 3 | 12 | 4 | 3 | 0.28 | 4 | 3 | 0 | 2 | 8 | 12 | 8 | 64 | 189 | 31 | 123 | 46 | 100 | 35 | 67 | 32 | 58 | 11 | 4 | 2 | 20 |
322,508 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_pca.py | sklearn.decomposition._pca.PCA | from numbers import Integral, Real
from scipy.sparse import issparse
from ..utils.validation import check_is_fitted, validate_data
from scipy import linalg
from ..utils._array_api import _convert_to_numpy, get_namespace
import numpy as np
from ..utils.sparsefuncs import _implicit_column_offset, mean_variance_axis
from ... |
class PCA(_BasePCA):
'''Principal component analysis (PCA).
Linear dimensionality reduction using Singular Value Decomposition of the
data to project it to a lower dimensional space. The input data is centered
but not scaled for each feature before applying the SVD.
It uses the LAPACK implementatio... | 12 | 8 | 50 | 5 | 27 | 18 | 5 | 1.37 | 1 | 5 | 0 | 0 | 9 | 18 | 9 | 72 | 745 | 114 | 268 | 76 | 244 | 367 | 160 | 62 | 150 | 12 | 4 | 2 | 41 |
322,509 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_sparse_pca.py | sklearn.decomposition._sparse_pca.MiniBatchSparsePCA | from ._dict_learning import MiniBatchDictionaryLearning, dict_learning
from ..utils._param_validation import Interval, StrOptions
from numbers import Integral, Real
import numpy as np
class MiniBatchSparsePCA(_BaseSparsePCA):
"""Mini-batch Sparse Principal Components Analysis.
Finds the set of sparse componen... |
class MiniBatchSparsePCA(_BaseSparsePCA):
'''Mini-batch Sparse Principal Components Analysis.
Finds the set of sparse components that can optimally reconstruct
the data. The amount of sparseness is controllable by the coefficient
of the L1 penalty, given by the parameter alpha.
For an example comp... | 3 | 2 | 32 | 2 | 30 | 1 | 1 | 1.51 | 1 | 2 | 1 | 0 | 2 | 13 | 2 | 44 | 210 | 39 | 68 | 35 | 49 | 103 | 19 | 13 | 16 | 1 | 3 | 0 | 2 |
322,510 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_sparse_pca.py | sklearn.decomposition._sparse_pca.SparsePCA | import numpy as np
from ._dict_learning import MiniBatchDictionaryLearning, dict_learning
from ..utils.extmath import svd_flip
class SparsePCA(_BaseSparsePCA):
"""Sparse Principal Components Analysis (SparsePCA).
Finds the set of sparse components that can optimally reconstruct
the data. The amount of sp... |
class SparsePCA(_BaseSparsePCA):
'''Sparse Principal Components Analysis (SparsePCA).
Finds the set of sparse components that can optimally reconstruct
the data. The amount of sparseness is controllable by the coefficient
of the L1 penalty, given by the parameter alpha.
Read more in the :ref:`User... | 3 | 2 | 29 | 1 | 27 | 1 | 2 | 1.51 | 1 | 1 | 0 | 0 | 2 | 12 | 2 | 44 | 178 | 30 | 59 | 33 | 42 | 89 | 18 | 13 | 15 | 3 | 3 | 0 | 4 |
322,511 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_sparse_pca.py | sklearn.decomposition._sparse_pca._BaseSparsePCA | from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from ..utils._param_validation import Interval, StrOptions
from ..utils import check_random_state
from ..linear_model import ridge_regression
from numbers import Integral, Real
from ..utils.validation import check_array, c... |
class _BaseSparsePCA(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator):
'''Base class for SparsePCA and MiniBatchSparsePCA'''
def __init__(self, n_components=None, *, alpha=1, ridge_alpha=0.01, max_iter=1000, tol=1e-08, method='lars', n_jobs=None, verbose=False, random_state=None):
pas... | 9 | 5 | 19 | 3 | 8 | 7 | 1 | 0.69 | 3 | 1 | 0 | 2 | 6 | 10 | 6 | 42 | 133 | 25 | 64 | 36 | 43 | 44 | 37 | 22 | 30 | 2 | 2 | 1 | 7 |
322,512 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/decomposition/_truncated_svd.py | sklearn.decomposition._truncated_svd.TruncatedSVD | from ..base import BaseEstimator, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from ..utils.validation import check_is_fitted, validate_data
from ..utils.extmath import _randomized_svd, safe_sparse_dot, svd_flip
import numpy as np
import scipy.sparse as sp
from ..utils._param_validation import Interv... |
class TruncatedSVD(ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimator):
'''Dimensionality reduction using truncated SVD (aka LSA).
This transformer performs linear dimensionality reduction by means of
truncated singular value decomposition (SVD). Contrary to PCA, this
estimator does not c... | 10 | 6 | 21 | 2 | 11 | 8 | 2 | 1.83 | 3 | 2 | 0 | 0 | 7 | 11 | 7 | 43 | 295 | 50 | 87 | 38 | 67 | 159 | 51 | 26 | 43 | 6 | 2 | 2 | 12 |
322,513 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/discriminant_analysis.py | sklearn.discriminant_analysis.DiscriminantAnalysisPredictionMixin | import numpy as np
class DiscriminantAnalysisPredictionMixin:
"""Mixin class for QuadraticDiscriminantAnalysis and NearestCentroid."""
def decision_function(self, X):
"""Apply decision function to an array of samples.
Parameters
----------
X : {array-like, sparse matrix} of sh... |
class DiscriminantAnalysisPredictionMixin:
'''Mixin class for QuadraticDiscriminantAnalysis and NearestCentroid.'''
def decision_function(self, X):
'''Apply decision function to an array of samples.
Parameters
----------
X : {array-like, sparse matrix} of shape (n_samples, n_fe... | 5 | 5 | 18 | 2 | 4 | 11 | 1 | 2.71 | 0 | 0 | 0 | 2 | 4 | 0 | 4 | 4 | 76 | 13 | 17 | 9 | 12 | 46 | 15 | 9 | 10 | 2 | 0 | 1 | 5 |
322,514 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/discriminant_analysis.py | sklearn.discriminant_analysis.LinearDiscriminantAnalysis | from .utils.extmath import softmax
from .utils.multiclass import check_classification_targets, unique_labels
import numpy as np
import warnings
from numbers import Integral, Real
from .utils._param_validation import HasMethods, Interval, StrOptions
from .linear_model._base import LinearClassifierMixin
from .base import... |
class LinearDiscriminantAnalysis(ClassNamePrefixFeaturesOutMixin, LinearClassifierMixin, TransformerMixin, BaseEstimator):
'''Linear Discriminant Analysis.
A classifier with a linear decision boundary, generated by fitting class
conditional densities to the data and using Bayes' rule.
The model fits a ... | 12 | 9 | 40 | 6 | 19 | 17 | 3 | 1.39 | 4 | 6 | 0 | 0 | 10 | 18 | 10 | 51 | 588 | 107 | 205 | 82 | 177 | 285 | 133 | 65 | 122 | 13 | 2 | 2 | 32 |
322,515 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/discriminant_analysis.py | sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis | from .base import BaseEstimator, ClassifierMixin, ClassNamePrefixFeaturesOutMixin, TransformerMixin, _fit_context
from numbers import Integral, Real
import numpy as np
from .utils._param_validation import HasMethods, Interval, StrOptions
from .utils.validation import check_is_fitted, validate_data
from scipy import lin... |
class QuadraticDiscriminantAnalysis(DiscriminantAnalysisPredictionMixin, ClassifierMixin, BaseEstimator):
'''Quadratic Discriminant Analysis.
A classifier with a quadratic decision boundary, generated
by fitting class conditional densities to the data
and using Bayes' rule.
The model fits a Gaussia... | 9 | 6 | 24 | 2 | 12 | 10 | 2 | 1.68 | 3 | 5 | 0 | 0 | 7 | 10 | 7 | 44 | 291 | 48 | 91 | 45 | 78 | 153 | 69 | 40 | 61 | 9 | 2 | 2 | 16 |
322,516 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/dummy.py | sklearn.dummy.DummyClassifier | from .utils.validation import _check_sample_weight, _num_samples, check_array, check_consistent_length, check_is_fitted, validate_data
from .utils.random import _random_choice_csc
import numpy as np
from .utils._param_validation import Interval, StrOptions
from numbers import Integral, Real
import warnings
from .utils.... |
class DummyClassifier(MultiOutputMixin, ClassifierMixin, BaseEstimator):
'''DummyClassifier makes predictions that ignore the input features.
This classifier serves as a simple baseline to compare against other more
complex classifiers.
The specific behavior of the baseline is selected with the `strate... | 9 | 6 | 42 | 7 | 24 | 11 | 6 | 0.96 | 3 | 4 | 0 | 4 | 7 | 9 | 7 | 41 | 425 | 77 | 178 | 42 | 169 | 170 | 119 | 41 | 111 | 14 | 2 | 3 | 41 |
322,517 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/dummy.py | sklearn.dummy.DummyRegressor | from .utils._param_validation import Interval, StrOptions
from .base import BaseEstimator, ClassifierMixin, MultiOutputMixin, RegressorMixin, _fit_context
from .utils.stats import _weighted_percentile
import numpy as np
from numbers import Integral, Real
from .utils.validation import _check_sample_weight, _num_samples,... |
class DummyRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
'''Regressor that makes predictions using simple rules.
This regressor is useful as a simple baseline to compare with other
(real) regressors. Do not use it for real problems.
Read more in the :ref:`User Guide <dummy_estimators>`.
... | 7 | 4 | 33 | 6 | 16 | 11 | 4 | 1.12 | 3 | 4 | 0 | 4 | 5 | 5 | 5 | 39 | 244 | 47 | 93 | 18 | 86 | 104 | 54 | 17 | 48 | 13 | 2 | 2 | 20 |
322,518 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_bagging.py | sklearn.ensemble._bagging.BaggingClassifier | from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_params, _routing_enabled, get_routing_for_object, process_routing
from ..utils.multiclass import check_classification_targets
from ..base import ClassifierMixin, RegressorMixin, _fit_context
from ..utils import Bunch, _safe_indexing, check_r... |
class BaggingClassifier(ClassifierMixin, BaseBagging):
'''A Bagging classifier.
A Bagging classifier is an ensemble meta-estimator that fits base
classifiers each on random subsets of the original dataset and then
aggregate their individual predictions (either by voting or by averaging)
to form a f... | 10 | 6 | 41 | 7 | 21 | 13 | 2 | 1.37 | 2 | 6 | 3 | 0 | 8 | 5 | 8 | 78 | 506 | 103 | 170 | 55 | 144 | 233 | 78 | 37 | 69 | 6 | 5 | 4 | 19 |
322,519 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_bagging.py | sklearn.ensemble._bagging.BaggingRegressor | from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_params, _routing_enabled, get_routing_for_object, process_routing
from ..base import ClassifierMixin, RegressorMixin, _fit_context
from ..utils import Bunch, _safe_indexing, check_random_state, column_or_1d
import numpy as np
from ..utils.va... |
class BaggingRegressor(RegressorMixin, BaseBagging):
'''A Bagging regressor.
A Bagging regressor is an ensemble meta-estimator that fits base
regressors each on random subsets of the original dataset and then
aggregate their individual predictions (either by voting or by averaging)
to form a final ... | 5 | 3 | 31 | 5 | 20 | 7 | 2 | 1.81 | 2 | 6 | 3 | 0 | 4 | 3 | 4 | 74 | 286 | 58 | 81 | 30 | 62 | 147 | 33 | 16 | 28 | 3 | 5 | 1 | 8 |
322,520 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_bagging.py | sklearn.ensemble._bagging.BaseBagging | import numbers
from warnings import warn
import itertools
from ..utils import Bunch, _safe_indexing, check_random_state, column_or_1d
from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_params, _routing_enabled, get_routing_for_object, process_routing
from ..base import ClassifierMixin, Regre... |
class BaseBagging(BaseEnsemble, metaclass=ABCMeta):
'''Base class for Bagging meta-estimator.
Warning: This class should not be used directly. Use derived classes
instead.
'''
@abstractmethod
def __init__(self, estimator=None, n_estimators=10, *, max_samples=1.0, max_features=1.0, bootstrap=Tru... | 17 | 7 | 33 | 5 | 18 | 10 | 3 | 0.49 | 2 | 12 | 4 | 3 | 11 | 15 | 11 | 68 | 403 | 68 | 225 | 73 | 183 | 110 | 105 | 42 | 93 | 19 | 4 | 2 | 34 |
322,521 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_base.py | sklearn.ensemble._base.BaseEnsemble | from abc import ABCMeta, abstractmethod
from ..base import BaseEstimator, MetaEstimatorMixin, clone, is_classifier, is_regressor
class BaseEnsemble(MetaEstimatorMixin, BaseEstimator, metaclass=ABCMeta):
"""Base class for all ensemble classes.
Warning: This class should not be used directly. Use derived classe... |
class BaseEnsemble(MetaEstimatorMixin, BaseEstimator, metaclass=ABCMeta):
'''Base class for all ensemble classes.
Warning: This class should not be used directly. Use derived classes
instead.
Parameters
----------
estimator : object
The base estimator from which the ensemble is built.
... | 8 | 6 | 8 | 1 | 5 | 2 | 2 | 1.06 | 3 | 1 | 0 | 4 | 6 | 4 | 6 | 57 | 82 | 18 | 31 | 19 | 17 | 33 | 23 | 12 | 16 | 3 | 3 | 1 | 9 |
322,522 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_base.py | sklearn.ensemble._base._BaseHeterogeneousEnsemble | from ..base import BaseEstimator, MetaEstimatorMixin, clone, is_classifier, is_regressor
from ..utils.metaestimators import _BaseComposition
from ..utils._tags import get_tags
from abc import ABCMeta, abstractmethod
from ..utils import Bunch, check_random_state
class _BaseHeterogeneousEnsemble(MetaEstimatorMixin, _Bas... |
class _BaseHeterogeneousEnsemble(MetaEstimatorMixin, _BaseComposition, metaclass=ABCMeta):
'''Base class for heterogeneous ensemble of learners.
Parameters
----------
estimators : list of (str, estimator) tuples
The ensemble of estimators to use in the ensemble. Each element of the
list... | 9 | 4 | 17 | 2 | 8 | 7 | 2 | 1.07 | 3 | 9 | 1 | 2 | 6 | 1 | 6 | 62 | 130 | 19 | 54 | 16 | 43 | 58 | 31 | 12 | 24 | 6 | 4 | 2 | 14 |
322,523 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.BaseForest | from ..utils.parallel import Parallel, delayed
from ..utils._param_validation import Interval, RealNotInt, StrOptions
from ..exceptions import DataConversionWarning
from ..tree._tree import DOUBLE, DTYPE
from ._base import BaseEnsemble, _partition_estimators
from ..utils.multiclass import check_classification_targets, ... |
class BaseForest(MultiOutputMixin, BaseEnsemble, metaclass=ABCMeta):
'''
Base class for forests of trees.
Warning: This class should not be used directly. Use derived classes
instead.
'''
@abstractmethod
def __init__(self, estimator, n_estimators=100, *, estimator_params=tuple(), bootstrap=... | 18 | 9 | 40 | 5 | 23 | 12 | 4 | 0.52 | 3 | 8 | 2 | 3 | 12 | 16 | 12 | 70 | 514 | 72 | 291 | 76 | 259 | 151 | 136 | 55 | 123 | 23 | 4 | 2 | 44 |
322,524 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.ExtraTreesClassifier | from ..tree import BaseDecisionTree, DecisionTreeClassifier, DecisionTreeRegressor, ExtraTreeClassifier, ExtraTreeRegressor
from ..utils._param_validation import Interval, RealNotInt, StrOptions
class ExtraTreesClassifier(ForestClassifier):
"""
An extra-trees classifier.
This class implements a meta estim... |
class ExtraTreesClassifier(ForestClassifier):
'''
An extra-trees classifier.
This class implements a meta estimator that fits a number of
randomized decision trees (a.k.a. extra-trees) on various sub-samples
of the dataset and uses averaging to improve the predictive accuracy
and control over-f... | 2 | 1 | 59 | 1 | 58 | 0 | 1 | 3.4 | 1 | 2 | 1 | 0 | 1 | 10 | 1 | 81 | 382 | 74 | 70 | 35 | 46 | 238 | 15 | 13 | 13 | 1 | 6 | 0 | 1 |
322,525 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.ExtraTreesRegressor | from ..tree import BaseDecisionTree, DecisionTreeClassifier, DecisionTreeRegressor, ExtraTreeClassifier, ExtraTreeRegressor
class ExtraTreesRegressor(ForestRegressor):
"""
An extra-trees regressor.
This class implements a meta estimator that fits a number of
randomized decision trees (a.k.a. extra-tre... |
class ExtraTreesRegressor(ForestRegressor):
'''
An extra-trees regressor.
This class implements a meta estimator that fits a number of
randomized decision trees (a.k.a. extra-trees) on various sub-samples
of the dataset and uses averaging to improve the predictive accuracy
and control over-fitt... | 2 | 1 | 57 | 1 | 56 | 0 | 1 | 3.55 | 1 | 2 | 1 | 0 | 1 | 10 | 1 | 79 | 349 | 67 | 62 | 34 | 39 | 220 | 15 | 13 | 13 | 1 | 6 | 0 | 1 |
322,526 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.ForestClassifier | from ..utils.validation import _check_feature_names_in, _check_sample_weight, _num_samples, check_is_fitted, validate_data
from ..utils.parallel import Parallel, delayed
from ..base import ClassifierMixin, MultiOutputMixin, RegressorMixin, TransformerMixin, _fit_context, is_classifier
from ._base import BaseEnsemble, _... |
class ForestClassifier(ClassifierMixin, BaseForest, metaclass=ABCMeta):
'''
Base class for forest of trees-based classifiers.
Warning: This class should not be used directly. Use derived classes
instead.
'''
@abstractmethod
def __init__(self, estimator, n_estimators=100, *, estimator_params... | 11 | 6 | 31 | 4 | 17 | 10 | 3 | 0.65 | 3 | 7 | 1 | 2 | 7 | 6 | 8 | 80 | 267 | 44 | 135 | 50 | 110 | 88 | 78 | 33 | 69 | 9 | 5 | 3 | 25 |
322,527 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.ForestRegressor | from ..metrics import accuracy_score, r2_score
from ..tree._tree import DOUBLE, DTYPE
from ._base import BaseEnsemble, _partition_estimators
from ..utils.parallel import Parallel, delayed
from abc import ABCMeta, abstractmethod
from ..utils.validation import _check_feature_names_in, _check_sample_weight, _num_samples, ... |
class ForestRegressor(RegressorMixin, BaseForest, metaclass=ABCMeta):
'''
Base class for forest of trees-based regressors.
Warning: This class should not be used directly. Use derived classes
instead.
'''
@abstractmethod
def __init__(self, estimator, n_estimators=100, *, estimator_params=tu... | 9 | 5 | 25 | 3 | 12 | 10 | 2 | 0.89 | 3 | 3 | 1 | 2 | 5 | 4 | 6 | 78 | 164 | 24 | 74 | 32 | 52 | 66 | 39 | 16 | 32 | 3 | 5 | 1 | 11 |
322,528 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.RandomForestClassifier | from ..tree import BaseDecisionTree, DecisionTreeClassifier, DecisionTreeRegressor, ExtraTreeClassifier, ExtraTreeRegressor
from ..utils._param_validation import Interval, RealNotInt, StrOptions
class RandomForestClassifier(ForestClassifier):
"""
A random forest classifier.
A random forest is a meta estim... |
class RandomForestClassifier(ForestClassifier):
'''
A random forest classifier.
A random forest is a meta estimator that fits a number of decision tree
classifiers on various sub-samples of the dataset and uses averaging to
improve the predictive accuracy and control over-fitting.
Trees in the ... | 2 | 1 | 59 | 1 | 58 | 0 | 1 | 3.59 | 1 | 2 | 1 | 2 | 1 | 10 | 1 | 81 | 395 | 74 | 70 | 35 | 46 | 251 | 15 | 13 | 13 | 1 | 6 | 0 | 1 |
322,529 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.RandomForestRegressor | from ..tree import BaseDecisionTree, DecisionTreeClassifier, DecisionTreeRegressor, ExtraTreeClassifier, ExtraTreeRegressor
class RandomForestRegressor(ForestRegressor):
"""
A random forest regressor.
A random forest is a meta estimator that fits a number of decision tree
regressors on various sub-sam... |
class RandomForestRegressor(ForestRegressor):
'''
A random forest regressor.
A random forest is a meta estimator that fits a number of decision tree
regressors on various sub-samples of the dataset and uses averaging to
improve the predictive accuracy and control over-fitting.
Trees in the fore... | 2 | 1 | 57 | 1 | 56 | 0 | 1 | 3.82 | 1 | 2 | 1 | 0 | 1 | 10 | 1 | 79 | 369 | 70 | 62 | 34 | 39 | 237 | 15 | 13 | 13 | 1 | 6 | 0 | 1 |
322,530 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_forest.py | sklearn.ensemble._forest.RandomTreesEmbedding | from ..utils import check_random_state, compute_sample_weight
from ..preprocessing import OneHotEncoder
import numpy as np
from ..base import ClassifierMixin, MultiOutputMixin, RegressorMixin, TransformerMixin, _fit_context, is_classifier
from ..utils._param_validation import Interval, RealNotInt, StrOptions
from ..uti... |
class RandomTreesEmbedding(TransformerMixin, BaseForest):
'''
An ensemble of totally random trees.
An unsupervised transformation of a dataset to a high-dimensional
sparse representation. A datapoint is coded according to which leaf of
each tree it is sorted into. Using a one-hot encoding of the le... | 9 | 5 | 23 | 2 | 11 | 10 | 1 | 2.38 | 2 | 5 | 2 | 0 | 7 | 9 | 7 | 81 | 369 | 65 | 90 | 41 | 66 | 214 | 40 | 25 | 32 | 1 | 5 | 1 | 7 |
322,531 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_gb.py | sklearn.ensemble._gb.BaseGradientBoosting | from ..utils.validation import _check_sample_weight, check_is_fitted, validate_data
from ..base import ClassifierMixin, RegressorMixin, _fit_context, is_classifier
from ..utils import check_array, check_random_state, column_or_1d
import warnings
from ..utils._param_validation import HasMethods, Interval, StrOptions
fro... |
class BaseGradientBoosting(BaseEnsemble, metaclass=ABCMeta):
'''Abstract base class for Gradient Boosting.'''
@abstractmethod
def __init__(self, *, loss, learning_rate, n_estimators, criterion, min_samples_split, min_samples_leaf, min_weight_fraction_leaf, max_depth, min_impurity_decrease, init, subsample,... | 26 | 17 | 36 | 3 | 25 | 9 | 4 | 0.35 | 2 | 21 | 11 | 2 | 20 | 33 | 20 | 77 | 771 | 85 | 515 | 167 | 440 | 179 | 264 | 103 | 243 | 17 | 4 | 5 | 88 |
322,532 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_gb.py | sklearn.ensemble._gb.GradientBoostingClassifier | from ..preprocessing import LabelEncoder
from ..utils.validation import _check_sample_weight, check_is_fitted, validate_data
import numpy as np
from ..tree._tree import DOUBLE, DTYPE, TREE_LEAF
from ..utils._param_validation import HasMethods, Interval, StrOptions
from ..base import ClassifierMixin, RegressorMixin, _fi... |
class GradientBoostingClassifier(ClassifierMixin, BaseGradientBoosting):
'''Gradient Boosting for classification.
This algorithm builds an additive model in a forward stage-wise fashion; it
allows for the optimization of arbitrary differentiable loss functions. In
each stage ``n_classes_`` regression t... | 11 | 8 | 26 | 2 | 13 | 12 | 3 | 2.88 | 2 | 10 | 5 | 0 | 10 | 3 | 10 | 89 | 610 | 104 | 131 | 52 | 97 | 377 | 63 | 28 | 52 | 5 | 5 | 2 | 25 |
322,533 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_gb.py | sklearn.ensemble._gb.GradientBoostingRegressor | from ..base import ClassifierMixin, RegressorMixin, _fit_context, is_classifier
from ..utils.validation import _check_sample_weight, check_is_fitted, validate_data
from .._loss.loss import _LOSSES, AbsoluteError, ExponentialLoss, HalfBinomialLoss, HalfMultinomialLoss, HalfSquaredError, HuberLoss, PinballLoss
from ..uti... |
class GradientBoostingRegressor(RegressorMixin, BaseGradientBoosting):
'''Gradient Boosting for regression.
This estimator builds an additive model in a forward stage-wise fashion; it
allows for the optimization of arbitrary differentiable loss functions. In
each stage a regression tree is fit on the n... | 7 | 4 | 20 | 2 | 12 | 7 | 1 | 3.96 | 2 | 1 | 0 | 0 | 6 | 2 | 6 | 85 | 459 | 82 | 76 | 36 | 45 | 301 | 22 | 11 | 15 | 2 | 5 | 1 | 8 |
322,534 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_gb.py | sklearn.ensemble._gb.VerboseReporter | from time import time
class VerboseReporter:
"""Reports verbose output to stdout.
Parameters
----------
verbose : int
Verbosity level. If ``verbose==1`` output is printed once in a while
(when iteration mod verbose_mod is zero).; if larger than 1 then output
is printed for each... |
class VerboseReporter:
'''Reports verbose output to stdout.
Parameters
----------
verbose : int
Verbosity level. If ``verbose==1`` output is printed once in a while
(when iteration mod verbose_mod is zero).; if larger than 1 then output
is printed for each update.
'''
d... | 4 | 3 | 21 | 2 | 12 | 8 | 3 | 0.82 | 0 | 2 | 0 | 0 | 3 | 5 | 3 | 3 | 77 | 9 | 38 | 15 | 34 | 31 | 28 | 15 | 24 | 5 | 0 | 2 | 8 |
322,535 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_hist_gradient_boosting/binning.py | sklearn.ensemble._hist_gradient_boosting.binning._BinMapper | from ...utils.parallel import Parallel, delayed
from ._bitset import set_bitset_memoryview
from .common import ALMOST_INF, X_BINNED_DTYPE, X_BITSET_INNER_DTYPE, X_DTYPE
from ...utils.validation import check_is_fitted
from ._binning import _map_to_bins
from ...base import BaseEstimator, TransformerMixin
from ...utils._o... |
class _BinMapper(TransformerMixin, BaseEstimator):
'''Transformer that maps a dataset into integer-valued bins.
For continuous features, the bins are created in a feature-wise fashion,
using quantiles so that each bins contains approximately the same number
of samples. For large datasets, quantiles are... | 5 | 4 | 44 | 7 | 26 | 11 | 4 | 1.15 | 2 | 5 | 1 | 0 | 4 | 10 | 4 | 39 | 259 | 35 | 104 | 45 | 91 | 120 | 67 | 37 | 62 | 10 | 2 | 2 | 16 |
322,536 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py | sklearn.ensemble._hist_gradient_boosting.gradient_boosting.BaseHistGradientBoosting | from .grower import TreeGrower
from ...metrics import check_scoring
from .common import G_H_DTYPE, X_DTYPE, Y_DTYPE
from .binning import _BinMapper
from ...base import BaseEstimator, ClassifierMixin, RegressorMixin, _fit_context, is_classifier
from ._gradient_boosting import _update_raw_predictions
from ..._loss.loss i... |
class BaseHistGradientBoosting(BaseEstimator, ABC):
'''Base class for histogram-based gradient boosting estimators.'''
@abstractmethod
def __init__(self, loss, *, learning_rate, max_iter, max_leaf_nodes, max_depth, min_samples_leaf, l2_regularization, max_features, max_bins, categorical_features, monotonic... | 33 | 20 | 49 | 5 | 33 | 11 | 5 | 0.31 | 2 | 27 | 6 | 2 | 26 | 40 | 26 | 77 | 1,327 | 158 | 903 | 241 | 819 | 278 | 441 | 177 | 414 | 40 | 4 | 4 | 127 |
322,537 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py | sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier | from ..._loss.loss import _LOSSES, BaseLoss, HalfBinomialLoss, HalfGammaLoss, HalfMultinomialLoss, HalfPoissonLoss, PinballLoss
from ...utils import check_random_state, compute_sample_weight, resample
from ...preprocessing import FunctionTransformer, LabelEncoder, OrdinalEncoder
from ...utils.multiclass import check_cl... |
class HistGradientBoostingClassifier(ClassifierMixin, BaseHistGradientBoosting):
'''Histogram-based Gradient Boosting Classification Tree.
This estimator is much faster than
:class:`GradientBoostingClassifier<sklearn.ensemble.GradientBoostingClassifier>`
for big datasets (n_samples >= 10 000).
This... | 12 | 9 | 19 | 2 | 10 | 8 | 2 | 2.85 | 2 | 5 | 3 | 0 | 11 | 4 | 11 | 90 | 499 | 72 | 111 | 53 | 75 | 316 | 56 | 29 | 44 | 3 | 5 | 2 | 22 |
322,538 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py | sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingRegressor | from numbers import Integral, Real
from ...utils._param_validation import Interval, RealNotInt, StrOptions
from .common import G_H_DTYPE, X_DTYPE, Y_DTYPE
from ..._loss.loss import _LOSSES, BaseLoss, HalfBinomialLoss, HalfGammaLoss, HalfMultinomialLoss, HalfPoissonLoss, PinballLoss
from ...utils.validation import _chec... |
class HistGradientBoostingRegressor(RegressorMixin, BaseHistGradientBoosting):
'''Histogram-based Gradient Boosting Regression Tree.
This estimator is much faster than
:class:`GradientBoostingRegressor<sklearn.ensemble.GradientBoostingRegressor>`
for big datasets (n_samples >= 10 000).
This estimat... | 7 | 3 | 18 | 1 | 13 | 5 | 2 | 2.77 | 2 | 2 | 0 | 0 | 6 | 2 | 6 | 85 | 401 | 54 | 92 | 35 | 61 | 255 | 26 | 11 | 19 | 5 | 5 | 2 | 12 |
322,539 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_hist_gradient_boosting/grower.py | sklearn.ensemble._hist_gradient_boosting.grower.TreeGrower | import numbers
from .splitting import Splitter
from timeit import default_timer as time
from .histogram import HistogramBuilder
from .predictor import TreePredictor
from .common import PREDICTOR_RECORD_DTYPE, X_BITSET_INNER_DTYPE, MonotonicConstraint
import numpy as np
from sklearn.utils._openmp_helpers import _openmp_... |
class TreeGrower:
'''Tree grower class used to build a tree.
The tree is fitted to predict the values of a Newton-Raphson step. The
splits are considered in a best-first fashion, and the quality of a
split is defined in splitting._split_gain.
Parameters
----------
X_binned : ndarray of shap... | 12 | 11 | 44 | 4 | 31 | 10 | 4 | 0.57 | 0 | 8 | 2 | 0 | 11 | 26 | 11 | 11 | 596 | 61 | 344 | 102 | 306 | 197 | 192 | 74 | 180 | 16 | 0 | 3 | 47 |
322,540 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_hist_gradient_boosting/grower.py | sklearn.ensemble._hist_gradient_boosting.grower.TreeNode | class TreeNode:
"""Tree Node class used in TreeGrower.
This isn't used for prediction purposes, only for training (see
TreePredictor).
Parameters
----------
depth : int
The depth of the node, i.e. its distance from the root.
sample_indices : ndarray of shape (n_samples_at_node,), d... | class TreeNode:
'''Tree Node class used in TreeGrower.
This isn't used for prediction purposes, only for training (see
TreePredictor).
Parameters
----------
depth : int
The depth of the node, i.e. its distance from the root.
sample_indices : ndarray of shape (n_samples_at_node,), dty... | 4 | 3 | 19 | 1 | 11 | 7 | 1 | 2.21 | 0 | 1 | 0 | 0 | 3 | 17 | 3 | 3 | 116 | 10 | 33 | 31 | 19 | 73 | 23 | 21 | 19 | 1 | 0 | 0 | 3 |
322,541 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_hist_gradient_boosting/predictor.py | sklearn.ensemble._hist_gradient_boosting.predictor.TreePredictor | import numpy as np
from ._predictor import _compute_partial_dependence, _predict_from_binned_data, _predict_from_raw_data
from .common import PREDICTOR_RECORD_DTYPE, Y_DTYPE
class TreePredictor:
"""Tree class used for predictions.
Parameters
----------
nodes : ndarray of PREDICTOR_RECORD_DTYPE
... |
class TreePredictor:
'''Tree class used for predictions.
Parameters
----------
nodes : ndarray of PREDICTOR_RECORD_DTYPE
The nodes of the tree.
binned_left_cat_bitsets : ndarray of shape (n_categorical_splits, 8), dtype=uint32
Array of bitsets for binned categories used in predict_b... | 8 | 6 | 15 | 1 | 6 | 8 | 1 | 1.71 | 0 | 3 | 0 | 0 | 7 | 3 | 7 | 7 | 129 | 18 | 41 | 13 | 33 | 70 | 26 | 13 | 18 | 3 | 0 | 1 | 9 |
322,542 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_iforest.py | sklearn.ensemble._iforest.IsolationForest | from warnings import warn
import numpy as np
from scipy.sparse import issparse
from ..base import OutlierMixin, _fit_context
from ..utils._param_validation import Interval, RealNotInt, StrOptions
from ..utils import check_array, check_random_state, gen_batches
from ..tree import ExtraTreeRegressor
import threading
from... |
class IsolationForest(OutlierMixin, BaseBagging):
'''
Isolation Forest Algorithm.
Return the anomaly score of each sample using the IsolationForest algorithm
The IsolationForest 'isolates' observations by randomly selecting a feature
and then randomly selecting a split value between the maximum and... | 14 | 7 | 32 | 5 | 13 | 14 | 2 | 1.69 | 2 | 9 | 2 | 0 | 12 | 7 | 12 | 82 | 584 | 108 | 177 | 52 | 151 | 300 | 74 | 37 | 61 | 7 | 5 | 2 | 21 |
322,543 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_stacking.py | sklearn.ensemble._stacking.StackingClassifier | from ..utils import Bunch
from ..utils.multiclass import check_classification_targets, type_of_target
from ..utils._param_validation import HasMethods, StrOptions
from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_params, _routing_enabled, process_routing
import numpy as np
from ..base impor... | null | 13 | 7 | 24 | 3 | 11 | 10 | 2 | 2.03 | 2 | 8 | 3 | 0 | 9 | 2 | 9 | 88 | 417 | 68 | 115 | 43 | 82 | 234 | 55 | 20 | 45 | 3 | 6 | 1 | 17 |
322,544 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_stacking.py | sklearn.ensemble._stacking.StackingRegressor | from ..base import ClassifierMixin, RegressorMixin, TransformerMixin, _fit_context, clone, is_classifier, is_regressor
from ..linear_model import LogisticRegression, RidgeCV
from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_params, _routing_enabled, process_routing
from ..utils import Bunch... | null | 9 | 5 | 22 | 4 | 7 | 11 | 1 | 3.47 | 2 | 4 | 2 | 0 | 7 | 0 | 7 | 86 | 305 | 59 | 55 | 23 | 35 | 191 | 29 | 11 | 21 | 2 | 6 | 1 | 10 |
322,545 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_stacking.py | sklearn.ensemble._stacking._BaseStacking | from ..exceptions import NotFittedError
from ..base import ClassifierMixin, RegressorMixin, TransformerMixin, _fit_context, clone, is_classifier, is_regressor
from abc import ABCMeta, abstractmethod
import scipy.sparse as sparse
from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_params, _rou... | null | 17 | 8 | 31 | 4 | 18 | 10 | 4 | 0.51 | 3 | 13 | 6 | 2 | 10 | 12 | 11 | 77 | 371 | 52 | 211 | 73 | 180 | 108 | 119 | 51 | 107 | 12 | 5 | 3 | 39 |
322,546 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_voting.py | sklearn.ensemble._voting.VotingClassifier | from ..preprocessing import LabelEncoder
import numpy as np
from ..utils.validation import _check_feature_names_in, check_is_fitted, column_or_1d
from ..utils.metaestimators import available_if
from ..utils.multiclass import type_of_target
from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_p... |
class VotingClassifier(ClassifierMixin, _BaseVoting):
'''Soft Voting/Majority Rule classifier for unfitted estimators.
Read more in the :ref:`User Guide <voting_classifier>`.
.. versionadded:: 0.17
Parameters
----------
estimators : list of (str, estimator) tuples
Invoking the ``fit`` m... | 12 | 7 | 22 | 3 | 10 | 8 | 2 | 1.74 | 2 | 6 | 1 | 0 | 9 | 7 | 9 | 85 | 346 | 62 | 104 | 42 | 81 | 181 | 61 | 29 | 51 | 3 | 6 | 2 | 17 |
322,547 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_voting.py | sklearn.ensemble._voting.VotingRegressor | from ..utils.metadata_routing import MetadataRouter, MethodMapping, _raise_for_params, _routing_enabled, process_routing
from ..utils.validation import _check_feature_names_in, check_is_fitted, column_or_1d
from ..base import ClassifierMixin, RegressorMixin, TransformerMixin, _fit_context, clone
import numpy as np
cla... |
class VotingRegressor(RegressorMixin, _BaseVoting):
'''Prediction voting regressor for unfitted estimators.
A voting regressor is an ensemble meta-estimator that fits several base
regressors, each on the whole dataset. Then it averages the individual
predictions to form a final prediction.
For a de... | 7 | 5 | 18 | 3 | 5 | 11 | 1 | 4.63 | 2 | 1 | 0 | 0 | 5 | 3 | 5 | 81 | 193 | 41 | 27 | 14 | 18 | 125 | 21 | 10 | 15 | 1 | 6 | 0 | 5 |
322,548 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_voting.py | sklearn.ensemble._voting._BaseVoting | import numpy as np
from ..utils.validation import _check_feature_names_in, check_is_fitted, column_or_1d
from ..utils import Bunch
from abc import abstractmethod
from ..base import ClassifierMixin, RegressorMixin, TransformerMixin, _fit_context, clone
from numbers import Integral
from ..utils._repr_html.estimator impor... |
class _BaseVoting(TransformerMixin, _BaseHeterogeneousEnsemble):
'''Base class for voting.
Warning: This class should not be used directly. Use derived classes
instead.
'''
def _log_message(self, name, idx, total):
pass
@property
def _weights_not_none(self):
'''Get the weig... | 12 | 7 | 15 | 2 | 9 | 4 | 2 | 0.47 | 2 | 11 | 6 | 2 | 8 | 4 | 8 | 74 | 145 | 27 | 80 | 27 | 68 | 38 | 48 | 22 | 39 | 8 | 5 | 3 | 19 |
322,549 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_weight_boosting.py | sklearn.ensemble._weight_boosting.AdaBoostClassifier | from ..utils.validation import _check_sample_weight, _num_samples, check_is_fitted, has_fit_parameter, validate_data
import warnings
from ..tree import DecisionTreeClassifier, DecisionTreeRegressor
from ..utils._param_validation import HasMethods, Hidden, Interval, StrOptions
import numpy as np
from ..utils.metadata_ro... |
class AdaBoostClassifier(_RoutingNotSupportedMixin, ClassifierMixin, BaseWeightBoosting):
'''An AdaBoost classifier.
An AdaBoost [1]_ classifier is a meta-estimator that begins by fitting a
classifier on the original dataset and then fits additional copies of the
classifier on the same dataset but wher... | 13 | 11 | 33 | 6 | 12 | 14 | 3 | 1.88 | 3 | 5 | 1 | 0 | 10 | 3 | 11 | 78 | 523 | 109 | 144 | 51 | 121 | 270 | 95 | 40 | 83 | 6 | 5 | 2 | 30 |
322,550 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_weight_boosting.py | sklearn.ensemble._weight_boosting.AdaBoostRegressor | import numpy as np
from ..utils.extmath import softmax, stable_cumsum
from ..tree import DecisionTreeClassifier, DecisionTreeRegressor
from ..utils.metadata_routing import _raise_for_unsupported_routing, _RoutingNotSupportedMixin
from ..utils.validation import _check_sample_weight, _num_samples, check_is_fitted, has_fi... |
class AdaBoostRegressor(_RoutingNotSupportedMixin, RegressorMixin, BaseWeightBoosting):
'''An AdaBoost regressor.
An AdaBoost [1] regressor is a meta-estimator that begins by fitting a
regressor on the original dataset and then fits additional copies of the
regressor on the same dataset but where the w... | 7 | 5 | 30 | 6 | 12 | 12 | 2 | 2.06 | 3 | 3 | 1 | 0 | 6 | 2 | 6 | 73 | 307 | 68 | 78 | 38 | 63 | 161 | 53 | 30 | 46 | 8 | 5 | 2 | 14 |
322,551 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/ensemble/_weight_boosting.py | sklearn.ensemble._weight_boosting.BaseWeightBoosting | from ..utils.metadata_routing import _raise_for_unsupported_routing, _RoutingNotSupportedMixin
from ._base import BaseEnsemble
from numbers import Integral, Real
import warnings
import numpy as np
from ..metrics import accuracy_score, r2_score
from ..utils import _safe_indexing, check_random_state
from ..base import Cl... |
class BaseWeightBoosting(BaseEnsemble, metaclass=ABCMeta):
'''Base class for AdaBoost estimators.
Warning: This class should not be used directly. Use derived classes
instead.
'''
@abstractmethod
def __init__(self, estimator=None, *, n_estimators=50, estimator_params=tuple(), learning_rate=1.0,... | 12 | 5 | 33 | 5 | 16 | 12 | 2 | 0.73 | 2 | 7 | 0 | 2 | 7 | 6 | 7 | 64 | 260 | 47 | 123 | 38 | 101 | 90 | 59 | 23 | 51 | 7 | 4 | 2 | 17 |
322,552 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.ConvergenceWarning | class ConvergenceWarning(UserWarning):
"""Custom warning to capture convergence problems
.. versionchanged:: 0.18
Moved from sklearn.utils.
""" | class ConvergenceWarning(UserWarning):
'''Custom warning to capture convergence problems
.. versionchanged:: 0.18
Moved from sklearn.utils.
'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 6 | 1 | 1 | 1 | 0 | 4 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,553 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.DataConversionWarning | class DataConversionWarning(UserWarning):
"""Warning used to notify implicit data conversions happening in the code.
This warning occurs when some input data needs to be converted or
interpreted in a way that may not match the user's expectations.
For example, this warning may occur when the user
... | class DataConversionWarning(UserWarning):
'''Warning used to notify implicit data conversions happening in the code.
This warning occurs when some input data needs to be converted or
interpreted in a way that may not match the user's expectations.
For example, this warning may occur when the user
... | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 16 | 3 | 1 | 1 | 0 | 12 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,554 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.DataDimensionalityWarning | class DataDimensionalityWarning(UserWarning):
"""Custom warning to notify potential issues with data dimensionality.
For example, in random projection, this warning is raised when the
number of components, which quantifies the dimensionality of the target
projection space, is higher than the number of ... | class DataDimensionalityWarning(UserWarning):
'''Custom warning to notify potential issues with data dimensionality.
For example, in random projection, this warning is raised when the
number of components, which quantifies the dimensionality of the target
projection space, is higher than the number of f... | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 9 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 12 | 2 | 1 | 1 | 0 | 9 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,555 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.EfficiencyWarning | class EfficiencyWarning(UserWarning):
"""Warning used to notify the user of inefficient computation.
This warning notifies the user that the efficiency may not be optimal due
to some reason which may be included as a part of the warning message.
This may be subclassed into a more specific Warning class... | class EfficiencyWarning(UserWarning):
'''Warning used to notify the user of inefficient computation.
This warning notifies the user that the efficiency may not be optimal due
to some reason which may be included as a part of the warning message.
This may be subclassed into a more specific Warning class.... | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 9 | 2 | 1 | 1 | 0 | 6 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,556 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.EstimatorCheckFailedWarning | class EstimatorCheckFailedWarning(UserWarning):
"""Warning raised when an estimator check from the common tests fails.
Parameters
----------
estimator : estimator object
Estimator instance for which the test failed.
check_name : str
Name of the check that failed.
exception : E... | class EstimatorCheckFailedWarning(UserWarning):
'''Warning raised when an estimator check from the common tests fails.
Parameters
----------
estimator : estimator object
Estimator instance for which the test failed.
check_name : str
Name of the check that failed.
exception : Exce... | 4 | 1 | 10 | 0 | 10 | 0 | 1 | 0.53 | 1 | 2 | 0 | 0 | 3 | 6 | 3 | 15 | 55 | 9 | 30 | 20 | 17 | 16 | 13 | 11 | 9 | 2 | 5 | 0 | 4 |
322,557 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.FitFailedWarning | class FitFailedWarning(RuntimeWarning):
"""Warning class used if there is an error while fitting the estimator.
This Warning is used in meta estimators GridSearchCV and RandomizedSearchCV
and the cross-validation helper function cross_val_score to warn when there
is an error while fitting the estimator... | class FitFailedWarning(RuntimeWarning):
'''Warning class used if there is an error while fitting the estimator.
This Warning is used in meta estimators GridSearchCV and RandomizedSearchCV
and the cross-validation helper function cross_val_score to warn when there
is an error while fitting the estimator.... | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 10 | 2 | 1 | 1 | 0 | 7 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,558 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.InconsistentVersionWarning | class InconsistentVersionWarning(UserWarning):
"""Warning raised when an estimator is unpickled with an inconsistent version.
Parameters
----------
estimator_name : str
Estimator name.
current_sklearn_version : str
Current scikit-learn version.
original_sklearn_version : str
... | class InconsistentVersionWarning(UserWarning):
'''Warning raised when an estimator is unpickled with an inconsistent version.
Parameters
----------
estimator_name : str
Estimator name.
current_sklearn_version : str
Current scikit-learn version.
original_sklearn_version : str
... | 3 | 1 | 9 | 0 | 9 | 1 | 1 | 0.61 | 1 | 0 | 0 | 0 | 2 | 3 | 2 | 14 | 33 | 5 | 18 | 8 | 13 | 11 | 7 | 6 | 4 | 1 | 5 | 0 | 2 |
322,559 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.NotFittedError | class NotFittedError(ValueError, AttributeError):
"""Exception class to raise if estimator is used before fitting.
This class inherits from both ValueError and AttributeError to help with
exception handling and backward compatibility.
Examples
--------
>>> from sklearn.svm import LinearSVC
... | class NotFittedError(ValueError, AttributeError):
'''Exception class to raise if estimator is used before fitting.
This class inherits from both ValueError and AttributeError to help with
exception handling and backward compatibility.
Examples
--------
>>> from sklearn.svm import LinearSVC
>... | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 16 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 20 | 3 | 1 | 1 | 0 | 16 | 1 | 1 | 0 | 0 | 4 | 0 | 0 |
322,560 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.PositiveSpectrumWarning | class PositiveSpectrumWarning(UserWarning):
"""Warning raised when the eigenvalues of a PSD matrix have issues
This warning is typically raised by ``_check_psd_eigenvalues`` when the
eigenvalues of a positive semidefinite (PSD) matrix such as a gram matrix
(kernel) present significant negative eigenval... | class PositiveSpectrumWarning(UserWarning):
'''Warning raised when the eigenvalues of a PSD matrix have issues
This warning is typically raised by ``_check_psd_eigenvalues`` when the
eigenvalues of a positive semidefinite (PSD) matrix such as a gram matrix
(kernel) present significant negative eigenvalu... | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 10 | 2 | 1 | 1 | 0 | 7 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,561 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.SkipTestWarning | class SkipTestWarning(UserWarning):
"""Warning class used to notify the user of a test that was skipped.
For example, one of the estimator checks requires a pandas import.
If the pandas package cannot be imported, the test will be skipped rather
than register as a failure.
""" | class SkipTestWarning(UserWarning):
'''Warning class used to notify the user of a test that was skipped.
For example, one of the estimator checks requires a pandas import.
If the pandas package cannot be imported, the test will be skipped rather
than register as a failure.
'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 7 | 1 | 1 | 1 | 0 | 5 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,562 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.UndefinedMetricWarning | class UndefinedMetricWarning(UserWarning):
"""Warning used when the metric is invalid
.. versionchanged:: 0.18
Moved from sklearn.base.
""" | class UndefinedMetricWarning(UserWarning):
'''Warning used when the metric is invalid
.. versionchanged:: 0.18
Moved from sklearn.base.
'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 6 | 1 | 1 | 1 | 0 | 4 | 1 | 1 | 0 | 0 | 5 | 0 | 0 |
322,563 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/exceptions.py | sklearn.exceptions.UnsetMetadataPassedError | class UnsetMetadataPassedError(ValueError):
"""Exception class to raise if a metadata is passed which is not explicitly requested (metadata=True) or not requested (metadata=False).
.. versionadded:: 1.3
Parameters
----------
message : str
The message
unrequested_params : dict
... | class UnsetMetadataPassedError(ValueError):
'''Exception class to raise if a metadata is passed which is not explicitly requested (metadata=True) or not requested (metadata=False).
.. versionadded:: 1.3
Parameters
----------
message : str
The message
unrequested_params : dict
... | 2 | 1 | 4 | 0 | 4 | 0 | 1 | 2.6 | 1 | 1 | 0 | 0 | 1 | 2 | 1 | 12 | 23 | 5 | 5 | 4 | 3 | 13 | 5 | 4 | 3 | 1 | 4 | 0 | 1 |
322,564 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.ArffDecoder | import re
class ArffDecoder:
"""An ARFF decoder."""
def __init__(self):
"""Constructor."""
self._conversors = []
self._current_line = 0
def _decode_comment(self, s):
"""(INTERNAL) Decodes a comment line.
Comments are single line strings starting, obligatorily, wit... |
class ArffDecoder:
'''An ARFF decoder.'''
def __init__(self):
'''Constructor.'''
pass
def _decode_comment(self, s):
'''(INTERNAL) Decodes a comment line.
Comments are single line strings starting, obligatorily, with the ``%``
character, and can have any symbol, inc... | 8 | 7 | 33 | 6 | 16 | 11 | 4 | 0.71 | 0 | 16 | 9 | 0 | 6 | 2 | 6 | 6 | 233 | 50 | 107 | 27 | 99 | 76 | 91 | 26 | 83 | 16 | 0 | 4 | 31 |
322,565 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.ArffEncoder | class ArffEncoder:
"""An ARFF encoder."""
def _encode_comment(self, s=''):
"""(INTERNAL) Encodes a comment line.
Comments are single line strings starting, obligatorily, with the ``%``
character, and can have any symbol, including whitespaces or special
characters.
If ... | class ArffEncoder:
'''An ARFF encoder.'''
def _encode_comment(self, s=''):
'''(INTERNAL) Encodes a comment line.
Comments are single line strings starting, obligatorily, with the ``%``
character, and can have any symbol, including whitespaces or special
characters.
If ``... | 6 | 6 | 27 | 6 | 11 | 9 | 4 | 0.83 | 0 | 5 | 1 | 0 | 5 | 0 | 5 | 5 | 140 | 34 | 58 | 15 | 52 | 48 | 52 | 15 | 46 | 12 | 0 | 3 | 22 |
322,566 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.ArffException | from typing import Optional, List, Dict, Any, Iterator, Union, Tuple
class ArffException(Exception):
message: Optional[str] = None
def __init__(self):
self.line = -1
def __str__(self):
return self.message % self.line |
class ArffException(Exception):
def __init__(self):
pass
def __str__(self):
pass | 3 | 0 | 2 | 0 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 11 | 2 | 1 | 2 | 12 | 8 | 2 | 6 | 5 | 3 | 0 | 6 | 5 | 3 | 1 | 3 | 0 | 2 |
322,567 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadAttributeFormat | class BadAttributeFormat(ArffException):
"""Error raised when some attribute declaration is in an invalid format."""
message = 'Bad @ATTRIBUTE format, at line %d.' | class BadAttributeFormat(ArffException):
'''Error raised when some attribute declaration is in an invalid format.'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 3 | 0 | 2 | 2 | 1 | 1 | 2 | 2 | 1 | 0 | 4 | 0 | 0 |
322,568 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadAttributeName | class BadAttributeName(ArffException):
"""Error raised when an attribute name is provided twice the attribute
declaration."""
def __init__(self, value, value2):
super().__init__()
self.message = 'Bad @ATTRIBUTE name %s at line' % value + ' %d, this name is already in use in line' + ' %d.' %... | class BadAttributeName(ArffException):
'''Error raised when an attribute name is provided twice the attribute
declaration.'''
def __init__(self, value, value2):
pass | 2 | 1 | 7 | 0 | 7 | 0 | 1 | 0.25 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 13 | 11 | 1 | 8 | 3 | 6 | 2 | 4 | 3 | 2 | 1 | 4 | 0 | 1 |
322,569 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadAttributeType | class BadAttributeType(ArffException):
"""Error raised when some invalid type is provided into the attribute
declaration."""
message = 'Bad @ATTRIBUTE type, at line %d.' | class BadAttributeType(ArffException):
'''Error raised when some invalid type is provided into the attribute
declaration.'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 4 | 0 | 2 | 2 | 1 | 2 | 2 | 2 | 1 | 0 | 4 | 0 | 0 |
322,570 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadDataFormat | class BadDataFormat(ArffException):
"""Error raised when some data instance is in an invalid format."""
def __init__(self, value):
super().__init__()
self.message = 'Bad @DATA instance format in line %d: ' + '%s' % value | class BadDataFormat(ArffException):
'''Error raised when some data instance is in an invalid format.'''
def __init__(self, value):
pass | 2 | 1 | 6 | 0 | 6 | 0 | 1 | 0.14 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 13 | 8 | 0 | 7 | 3 | 5 | 1 | 4 | 3 | 2 | 1 | 4 | 0 | 1 |
322,571 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadLayout | class BadLayout(ArffException):
"""Error raised when the layout of the ARFF file has something wrong."""
message = 'Invalid layout of the ARFF file, at line %d.'
def __init__(self, msg=''):
super().__init__()
if msg:
self.message = BadLayout.message + ' ' + msg.replace('%', '%%'... | class BadLayout(ArffException):
'''Error raised when the layout of the ARFF file has something wrong.'''
def __init__(self, msg=''):
pass | 2 | 1 | 4 | 0 | 4 | 0 | 2 | 0.17 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 13 | 8 | 1 | 6 | 3 | 4 | 1 | 6 | 3 | 4 | 2 | 4 | 1 | 2 |
322,572 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadNominalFormatting | class BadNominalFormatting(ArffException):
"""Error raised when a nominal value with space is not properly quoted."""
def __init__(self, value):
super().__init__()
self.message = 'Nominal data value "%s" not properly quoted in line ' % value + '%d.' | class BadNominalFormatting(ArffException):
'''Error raised when a nominal value with space is not properly quoted.'''
def __init__(self, value):
pass | 2 | 1 | 6 | 0 | 6 | 0 | 1 | 0.14 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 13 | 8 | 0 | 7 | 3 | 5 | 1 | 4 | 3 | 2 | 1 | 4 | 0 | 1 |
322,573 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadNominalValue | class BadNominalValue(ArffException):
"""Error raised when a value in used in some data instance but is not
declared into it respective attribute declaration."""
def __init__(self, value):
super().__init__()
self.message = 'Data value %s not found in nominal declaration, ' % value + 'at lin... | class BadNominalValue(ArffException):
'''Error raised when a value in used in some data instance but is not
declared into it respective attribute declaration.'''
def __init__(self, value):
pass | 2 | 1 | 6 | 0 | 6 | 0 | 1 | 0.29 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 13 | 10 | 1 | 7 | 3 | 5 | 2 | 4 | 3 | 2 | 1 | 4 | 0 | 1 |
322,574 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadNumericalValue | class BadNumericalValue(ArffException):
"""Error raised when and invalid numerical value is used in some data
instance."""
message = 'Invalid numerical value, at line %d.' | class BadNumericalValue(ArffException):
'''Error raised when and invalid numerical value is used in some data
instance.'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 4 | 0 | 2 | 2 | 1 | 2 | 2 | 2 | 1 | 0 | 4 | 0 | 0 |
322,575 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadObject | class BadObject(ArffException):
"""Error raised when the object representing the ARFF file has something
wrong."""
def __init__(self, msg='Invalid object.'):
self.msg = msg
def __str__(self):
return '%s' % self.msg | class BadObject(ArffException):
'''Error raised when the object representing the ARFF file has something
wrong.'''
def __init__(self, msg='Invalid object.'):
pass
def __str__(self):
pass | 3 | 1 | 2 | 0 | 2 | 0 | 1 | 0.4 | 1 | 0 | 0 | 0 | 2 | 1 | 2 | 14 | 8 | 1 | 5 | 4 | 2 | 2 | 5 | 4 | 2 | 1 | 4 | 0 | 2 |
322,576 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadRelationFormat | class BadRelationFormat(ArffException):
"""Error raised when the relation declaration is in an invalid format."""
message = 'Bad @RELATION format, at line %d.' | class BadRelationFormat(ArffException):
'''Error raised when the relation declaration is in an invalid format.'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 3 | 0 | 2 | 2 | 1 | 1 | 2 | 2 | 1 | 0 | 4 | 0 | 0 |
322,577 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.BadStringValue | class BadStringValue(ArffException):
"""Error raise when a string contains space but is not quoted."""
message = 'Invalid string value at line %d.' | class BadStringValue(ArffException):
'''Error raise when a string contains space but is not quoted.'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 3 | 0 | 2 | 2 | 1 | 1 | 2 | 2 | 1 | 0 | 4 | 0 | 0 |
322,578 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.COOData | class COOData:
def decode_rows(self, stream, conversors):
data, rows, cols = ([], [], [])
for i, row in enumerate(stream):
values = _parse_values(row)
if not isinstance(values, dict):
raise BadLayout()
if not values:
continue
... | class COOData:
def decode_rows(self, stream, conversors):
pass
def encode_data(self, data, attributes):
pass | 3 | 0 | 30 | 4 | 25 | 2 | 8 | 0.06 | 0 | 11 | 4 | 0 | 2 | 0 | 2 | 2 | 62 | 9 | 50 | 15 | 47 | 3 | 44 | 14 | 41 | 8 | 0 | 3 | 15 |
322,579 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.Data | class Data(_DataListMixin, DenseGeneratorData):
pass | class Data(_DataListMixin, DenseGeneratorData):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 0 | 2 | 1 | 1 | 0 | 2 | 1 | 1 | 0 | 1 | 0 | 0 |
322,580 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.DenseGeneratorData | class DenseGeneratorData:
"""Internal helper class to allow for different matrix types without
making the code a huge collection of if statements."""
def decode_rows(self, stream, conversors):
for row in stream:
values = _parse_values(row)
if isinstance(values, dict):
... | class DenseGeneratorData:
'''Internal helper class to allow for different matrix types without
making the code a huge collection of if statements.'''
def decode_rows(self, stream, conversors):
pass
@staticmethod
def _decode_values(values, conversors):
pass
def encode_data(s... | 5 | 2 | 18 | 2 | 13 | 3 | 5 | 0.25 | 0 | 8 | 3 | 1 | 2 | 0 | 3 | 3 | 60 | 10 | 40 | 13 | 35 | 10 | 31 | 11 | 27 | 6 | 0 | 3 | 15 |
322,581 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.EncodedNominalConversor | class EncodedNominalConversor:
def __init__(self, values):
self.values = {v: i for i, v in enumerate(values)}
self.values[0] = 0
def __call__(self, value):
try:
return self.values[value]
except KeyError:
raise BadNominalValue(value) | class EncodedNominalConversor:
def __init__(self, values):
pass
def __call__(self, value):
pass | 3 | 0 | 4 | 0 | 4 | 0 | 2 | 0 | 0 | 3 | 1 | 0 | 2 | 1 | 2 | 2 | 10 | 1 | 9 | 4 | 6 | 0 | 9 | 4 | 6 | 2 | 0 | 1 | 3 |
322,582 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.LODData | class LODData(_DataListMixin, LODGeneratorData):
pass | class LODData(_DataListMixin, LODGeneratorData):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 0 | 2 | 1 | 1 | 0 | 2 | 1 | 1 | 0 | 1 | 0 | 0 |
322,583 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.LODGeneratorData | class LODGeneratorData:
def decode_rows(self, stream, conversors):
for row in stream:
values = _parse_values(row)
if not isinstance(values, dict):
raise BadLayout()
try:
yield {key: None if value is None else conversors[key](value) for key... | class LODGeneratorData:
def decode_rows(self, stream, conversors):
pass
def encode_data(self, data, attributes):
pass | 3 | 0 | 20 | 3 | 17 | 1 | 6 | 0.03 | 0 | 8 | 4 | 1 | 2 | 0 | 2 | 2 | 41 | 6 | 34 | 13 | 31 | 1 | 29 | 12 | 26 | 7 | 0 | 3 | 12 |
322,584 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff.NominalConversor | class NominalConversor:
def __init__(self, values):
self.values = set(values)
self.zero_value = values[0]
def __call__(self, value):
if value not in self.values:
if value == 0:
return self.zero_value
raise BadNominalValue(value)
return st... | class NominalConversor:
def __init__(self, values):
pass
def __call__(self, value):
pass | 3 | 0 | 7 | 0 | 5 | 2 | 2 | 0.4 | 0 | 3 | 1 | 0 | 2 | 2 | 2 | 2 | 15 | 1 | 10 | 5 | 7 | 4 | 10 | 5 | 7 | 3 | 0 | 2 | 4 |
322,585 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_arff.py | sklearn.externals._arff._DataListMixin | class _DataListMixin:
"""Mixin to return a list from decode_rows instead of a generator"""
def decode_rows(self, stream, conversors):
return list(super().decode_rows(stream, conversors)) | class _DataListMixin:
'''Mixin to return a list from decode_rows instead of a generator'''
def decode_rows(self, stream, conversors):
pass | 2 | 1 | 2 | 0 | 2 | 0 | 1 | 0.33 | 0 | 2 | 0 | 2 | 1 | 0 | 1 | 1 | 4 | 0 | 3 | 2 | 1 | 1 | 3 | 2 | 1 | 1 | 0 | 0 | 1 |
322,586 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_packaging/_structures.py | sklearn.externals._packaging._structures.InfinityType | class InfinityType:
def __repr__(self) -> str:
return 'Infinity'
def __hash__(self) -> int:
return hash(repr(self))
def __lt__(self, other: object) -> bool:
return False
def __le__(self, other: object) -> bool:
return False
def __eq__(self, other: object) -> bool... | class InfinityType:
def __repr__(self) -> str:
pass
def __hash__(self) -> int:
pass
def __lt__(self, other: object) -> bool:
pass
def __le__(self, other: object) -> bool:
pass
def __eq__(self, other: object) -> bool:
pass
def __ne__(self, other: obje... | 10 | 0 | 2 | 0 | 2 | 0 | 1 | 0 | 0 | 4 | 0 | 0 | 9 | 0 | 9 | 9 | 27 | 8 | 19 | 10 | 9 | 0 | 19 | 10 | 9 | 1 | 0 | 0 | 9 |
322,587 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_packaging/_structures.py | sklearn.externals._packaging._structures.NegativeInfinityType | class NegativeInfinityType:
def __repr__(self) -> str:
return '-Infinity'
def __hash__(self) -> int:
return hash(repr(self))
def __lt__(self, other: object) -> bool:
return True
def __le__(self, other: object) -> bool:
return True
def __eq__(self, other: object) ... | class NegativeInfinityType:
def __repr__(self) -> str:
pass
def __hash__(self) -> int:
pass
def __lt__(self, other: object) -> bool:
pass
def __le__(self, other: object) -> bool:
pass
def __eq__(self, other: object) -> bool:
pass
def __ne__(self, oth... | 10 | 0 | 2 | 0 | 2 | 0 | 1 | 0 | 0 | 5 | 1 | 0 | 9 | 0 | 9 | 9 | 27 | 8 | 19 | 10 | 9 | 0 | 19 | 10 | 9 | 1 | 0 | 0 | 9 |
322,588 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_packaging/version.py | sklearn.externals._packaging.version.InvalidVersion | class InvalidVersion(ValueError):
"""
An invalid version was found, users should refer to PEP 440.
""" | class InvalidVersion(ValueError):
'''
An invalid version was found, users should refer to PEP 440.
'''
pass | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 4 | 0 | 1 | 1 | 0 | 3 | 1 | 1 | 0 | 0 | 4 | 0 | 0 |
322,589 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_packaging/version.py | sklearn.externals._packaging.version.LegacyVersion | import warnings
class LegacyVersion(_BaseVersion):
def __init__(self, version: str) -> None:
self._version = str(version)
self._key = _legacy_cmpkey(self._version)
warnings.warn('Creating a LegacyVersion has been deprecated and will be removed in the next major release', DeprecationWarning... |
class LegacyVersion(_BaseVersion):
def __init__(self, version: str) -> None:
pass
def __str__(self) -> str:
pass
def __repr__(self) -> str:
pass
@property
def public(self) -> str:
pass
@property
def base_version(self) -> str:
pass
@property
... | 26 | 0 | 3 | 0 | 2 | 0 | 1 | 0 | 1 | 4 | 0 | 0 | 14 | 2 | 14 | 21 | 60 | 14 | 46 | 28 | 20 | 0 | 31 | 17 | 16 | 1 | 1 | 0 | 14 |
322,590 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_packaging/version.py | sklearn.externals._packaging.version.Version | import re
from typing import Callable, Iterator, List, Optional, SupportsInt, Tuple, Union
class Version(_BaseVersion):
_regex = re.compile('^\\s*' + VERSION_PATTERN + '\\s*$', re.VERBOSE | re.IGNORECASE)
def __init__(self, version: str) -> None:
match = self._regex.search(version)
if not matc... |
class Version(_BaseVersion):
def __init__(self, version: str) -> None:
pass
def __repr__(self) -> str:
pass
def __str__(self) -> str:
pass
@property
def epoch(self) -> int:
pass
@property
def release(self) -> Tuple[int, ...]:
pass
@property
... | 32 | 0 | 6 | 1 | 4 | 1 | 2 | 0.12 | 1 | 5 | 1 | 0 | 17 | 2 | 17 | 24 | 134 | 31 | 92 | 41 | 60 | 11 | 61 | 27 | 43 | 6 | 1 | 1 | 31 |
322,591 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/_packaging/version.py | sklearn.externals._packaging.version._BaseVersion | from typing import Callable, Iterator, List, Optional, SupportsInt, Tuple, Union
class _BaseVersion:
_key: Union[CmpKey, LegacyCmpKey]
def __hash__(self) -> int:
return hash(self._key)
def __lt__(self, other: '_BaseVersion') -> bool:
if not isinstance(other, _BaseVersion):
ret... |
class _BaseVersion:
def __hash__(self) -> int:
pass
def __lt__(self, other: '_BaseVersion') -> bool:
pass
def __le__(self, other: '_BaseVersion') -> bool:
pass
def __eq__(self, other: object) -> bool:
pass
def __ge__(self, other: '_BaseVersion') -> bool:
... | 8 | 0 | 5 | 1 | 4 | 0 | 2 | 0.11 | 0 | 3 | 0 | 2 | 7 | 0 | 7 | 7 | 44 | 13 | 28 | 8 | 20 | 3 | 28 | 8 | 20 | 2 | 0 | 1 | 13 |
322,592 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_aliases.py | sklearn.externals.array_api_compat.common._aliases.UniqueAllResult | from typing import TYPE_CHECKING, Any, NamedTuple, Optional, Sequence, cast
from ._typing import Array, Device, DType, Namespace
class UniqueAllResult(NamedTuple):
values: Array
indices: Array
inverse_indices: Array
counts: Array |
class UniqueAllResult(NamedTuple):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 5 | 1 | 4 | 0 | 5 | 1 | 4 | 0 | 1 | 0 | 0 |
322,593 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_aliases.py | sklearn.externals.array_api_compat.common._aliases.UniqueCountsResult | from typing import TYPE_CHECKING, Any, NamedTuple, Optional, Sequence, cast
from ._typing import Array, Device, DType, Namespace
class UniqueCountsResult(NamedTuple):
values: Array
counts: Array |
class UniqueCountsResult(NamedTuple):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 2 | 0 | 3 | 1 | 2 | 0 | 1 | 0 | 0 |
322,594 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_aliases.py | sklearn.externals.array_api_compat.common._aliases.UniqueInverseResult | from typing import TYPE_CHECKING, Any, NamedTuple, Optional, Sequence, cast
from ._typing import Array, Device, DType, Namespace
class UniqueInverseResult(NamedTuple):
values: Array
inverse_indices: Array |
class UniqueInverseResult(NamedTuple):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 2 | 0 | 3 | 1 | 2 | 0 | 1 | 0 | 0 |
322,595 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_helpers.py | sklearn.externals.array_api_compat.common._helpers._dask_device | from typing import TYPE_CHECKING, Any, Final, Literal, SupportsIndex, TypeAlias, TypeGuard, TypeVar, cast, overload
class _dask_device:
def __repr__(self) -> Literal['DASK_DEVICE']:
return 'DASK_DEVICE' |
class _dask_device:
def __repr__(self) -> Literal['DASK_DEVICE']:
pass | 2 | 0 | 2 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 3 | 0 | 3 | 2 | 1 | 0 | 3 | 2 | 1 | 1 | 0 | 0 | 1 |
322,596 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_linalg.py | sklearn.externals.array_api_compat.common._linalg.EighResult | from typing import Literal, NamedTuple, cast
from ._typing import Array, DType, JustFloat, JustInt, Namespace
class EighResult(NamedTuple):
eigenvalues: Array
eigenvectors: Array |
class EighResult(NamedTuple):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 2 | 0 | 3 | 1 | 2 | 0 | 1 | 0 | 0 |
322,597 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_linalg.py | sklearn.externals.array_api_compat.common._linalg.QRResult | from typing import Literal, NamedTuple, cast
from ._typing import Array, DType, JustFloat, JustInt, Namespace
class QRResult(NamedTuple):
Q: Array
R: Array |
class QRResult(NamedTuple):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 2 | 0 | 3 | 1 | 2 | 0 | 1 | 0 | 0 |
322,598 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_linalg.py | sklearn.externals.array_api_compat.common._linalg.SVDResult | from ._typing import Array, DType, JustFloat, JustInt, Namespace
from typing import Literal, NamedTuple, cast
class SVDResult(NamedTuple):
U: Array
S: Array
Vh: Array |
class SVDResult(NamedTuple):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 1 | 3 | 0 | 4 | 1 | 3 | 0 | 1 | 0 | 0 |
322,599 | etsi-ai/etsi-watchdog | /Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/etsi-ai_etsi-watchdog/venv/Lib/site-packages/sklearn/externals/array_api_compat/common/_linalg.py | sklearn.externals.array_api_compat.common._linalg.SlogdetResult | from typing import Literal, NamedTuple, cast
from ._typing import Array, DType, JustFloat, JustInt, Namespace
class SlogdetResult(NamedTuple):
sign: Array
logabsdet: Array |
class SlogdetResult(NamedTuple):
pass | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 2 | 0 | 3 | 1 | 2 | 0 | 1 | 0 | 0 |
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