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Functions1,916 in github.com/automl/auto-sklearn

⨍ Functions 1,916◇ Types & classes 344↳ Endpoints 63
Method__init__
(self, n_neighbors, weights, p, random_state=None)
autosklearn/pipeline/components/classification/k_nearest_neighbors.py:15
Method__init__
(self, random_state=None, verbose=0)
autosklearn/pipeline/components/classification/gaussian_nb.py:12
Method__init__
(self, shrinkage, tol, shrinkage_factor=0.5, random_state=None)
autosklearn/pipeline/components/classification/lda.py:18
Method__init__
(self, reg_param, random_state=None)
autosklearn/pipeline/components/classification/qda.py:14
Method__init__
( self, criterion, min_samples_leaf, min_samples_split, max_features,
autosklearn/pipeline/components/classification/extra_trees.py:27
Method__init__
( self, hidden_layer_depth, num_nodes_per_layer, activation, alpha,
autosklearn/pipeline/components/classification/mlp.py:26
Method__init__
( self, penalty, loss, dual, tol, C, multi_class,
autosklearn/pipeline/components/classification/liblinear_svc.py:20
Method__init__
( self, n_estimators, learning_rate, algorithm, max_depth, random_state=None )
autosklearn/pipeline/components/classification/adaboost.py:16
Method__init__
(self, C, fit_intercept, tol, loss, average, random_state=None)
autosklearn/pipeline/components/classification/passive_aggressive.py:25
Method__init__
(self, alpha, fit_prior, random_state=None, verbose=0)
autosklearn/pipeline/components/classification/multinomial_nb.py:17
Method__init__
(self, random_state=None)
autosklearn/pipeline/components/feature_preprocessing/densifier.py:11
Method__init__
(self, keep_variance, whiten, random_state=None)
autosklearn/pipeline/components/feature_preprocessing/pca.py:17
Method__init__
This preprocessors does not change the data
autosklearn/pipeline/components/feature_preprocessing/no_preprocessing.py:11
Method__init__
(self, alpha, mode="fpr", score_func="chi2", random_state=None)
autosklearn/pipeline/components/feature_preprocessing/select_rates_classification.py:24
Method__init__
Parameters ---------- gamma: float Parameter of the rbf kernel to be approximated exp(-gamma * x^2) n_co
autosklearn/pipeline/components/feature_preprocessing/kitchen_sinks.py:16
Method__init__
( self, alpha, mode="percentile", score_func="f_regression", random_state=None )
autosklearn/pipeline/components/feature_preprocessing/select_rates_regression.py:18
Method__init__
( self, penalty, loss, dual, tol, C, multi_class,
autosklearn/pipeline/components/feature_preprocessing/liblinear_svc_preprocessor.py:19
Method__init__
( self, n_components, kernel, degree=3, gamma=0.25, coef0=0.0, random_state=None )
autosklearn/pipeline/components/feature_preprocessing/kernel_pca.py:20
Method__init__
( self, n_estimators, criterion, min_samples_leaf, min_samples_split,
autosklearn/pipeline/components/feature_preprocessing/extra_trees_preproc_for_classification.py:19
Method__init__
(self, target_dim, random_state=None)
autosklearn/pipeline/components/feature_preprocessing/truncatedSVD.py:12
Method__init__
( self, n_estimators, criterion, min_samples_leaf, min_samples_split,
autosklearn/pipeline/components/feature_preprocessing/extra_trees_preproc_for_regression.py:20
Method__init__
( self, kernel, n_components, gamma=1.0, degree=3, coef0=1, random_state=None )
autosklearn/pipeline/components/feature_preprocessing/nystroem_sampler.py:23
Method__init__
(self, algorithm, whiten, fun, n_components=None, random_state=None)
autosklearn/pipeline/components/feature_preprocessing/fast_ica.py:19
Method__init__
(self, degree, interaction_only, include_bias, random_state=None)
autosklearn/pipeline/components/feature_preprocessing/polynomial.py:16
Method__init__
Parameters: random state : ignored score_func : callable, Function taking two arrays X and y, and returning a pa
autosklearn/pipeline/components/feature_preprocessing/select_percentile_classification.py:29
Method__init__
( self, n_estimators, max_depth, min_samples_split, min_samples_leaf,
autosklearn/pipeline/components/feature_preprocessing/random_trees_embedding.py:18
Method__init__
Parameters: random state : ignored score_func : callable, Function taking two arrays X and y, and returning a pa
autosklearn/pipeline/components/feature_preprocessing/select_percentile_regression.py:22
Method__init__
(self, n_clusters, affinity, linkage, pooling_func, random_state=None)
autosklearn/pipeline/components/feature_preprocessing/feature_agglomeration.py:21
Method__init__
( self, feat_type: Optional[FEAT_TYPE_TYPE] = None, config: Optional[Configuration] =
autosklearn/pipeline/components/data_preprocessing/feature_type_numerical.py:39
Method__init__
( self, config: Optional[Configuration] = None, pipeline: Optional[BasePipeline] = Non
autosklearn/pipeline/components/data_preprocessing/feature_type.py:41
Method__init__
( self, feat_type: Optional[FEAT_TYPE_TYPE] = None, config: Optional[Configuration] =
autosklearn/pipeline/components/data_preprocessing/feature_type_text.py:36
Method__init__
( self, feat_type: Optional[FEAT_TYPE_TYPE] = None, config: Optional[Configuration] =
autosklearn/pipeline/components/data_preprocessing/feature_type_categorical.py:46
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None, )
autosklearn/pipeline/components/data_preprocessing/rescaling/power_transformer.py:14
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/rescaling/minmax.py:14
Method__init__
( self, n_quantiles: int, output_distribution: str, random_state: Optional[Uni
autosklearn/pipeline/components/data_preprocessing/rescaling/quantile_transformer.py:26
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/rescaling/normalize.py:14
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/rescaling/abstract_rescaling.py:15
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/rescaling/standardize.py:16
Method__init__
( self, q_min: float, q_max: float, random_state: Optional[Union[int, np.rando
autosklearn/pipeline/components/data_preprocessing/rescaling/robust_scaler.py:25
Method__init__
( self, strategy: str = "mean", random_state: Optional[Union[int, np.random.RandomStat
autosklearn/pipeline/components/data_preprocessing/imputation/numerical_imputation.py:14
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/imputation/categorical_imputation.py:22
Method__init__
( self, feat_type: Optional[FEAT_TYPE_TYPE] = None, random_state: Optional[Union[int,
autosklearn/pipeline/components/data_preprocessing/minority_coalescense/no_coalescense.py:13
Method__init__
( self, feat_type: Optional[FEAT_TYPE_TYPE] = None, minimum_fraction: float = 0.01,
autosklearn/pipeline/components/data_preprocessing/minority_coalescense/minority_coalescer.py:17
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/categorical_encoding/encoding.py:15
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/categorical_encoding/no_encoding.py:13
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/categorical_encoding/one_hot_encoding.py:16
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/variance_threshold/variance_threshold.py:14
Method__init__
( self, strategy: str = "none", random_state: Optional[Union[int, np.random.RandomStat
autosklearn/pipeline/components/data_preprocessing/balancing/balancing.py:21
Method__init__
( self, n_components: Optional[int] = None, random_state: Optional[Union[int, np.rando
autosklearn/pipeline/components/data_preprocessing/text_feature_reduction/truncated_svd.py:19
Method__init__
( self, random_state: Optional[Union[int, np.random.RandomState]] = None )
autosklearn/pipeline/components/data_preprocessing/category_shift/category_shift.py:20
Method__init__
( self, ngram_range_word: int = 1, ngram_range_char: int = 4, min_df: float =
autosklearn/pipeline/components/data_preprocessing/text_encoding/tfidf_encoding.py:21
Method__init__
(self, configuration, random_state, tie_break_order)
autosklearn/experimental/selector.py:42
Method__init__
(self, n_estimators, **kwargs)
autosklearn/experimental/selector.py:317
Method__init__
(self, selector, default_strategies: typing.List[str])
autosklearn/experimental/selector.py:336
Method__init__
(self, portfolio)
autosklearn/experimental/askl2.py:29
Method__init__
Parameters ---------- time_left_for_this_task : int, optional (default=3600) Time limit in seconds for the search
autosklearn/experimental/askl2.py:146
Method__init__
(self, f: SMACCallback)
autosklearn/util/smac_wrap.py:13
Method__init__
Parameters ---------- client : Client The client they passed in
autosklearn/util/dask.py:68
Method__init__
(self, n_jobs: int | None = None)
autosklearn/util/dask.py:91
Method__init__
Parameters ---------- name : str The name of the task
autosklearn/util/stopwatch.py:16
Method__init__
(self)
autosklearn/util/stopwatch.py:74
Method__init__
( self, package_name: str, installed_version: Union[str, LooseVersion], operat
autosklearn/util/dependencies.py:88
Method__init__
(self, name: str, host: str, port: int)
autosklearn/util/logging_.py:206
Method__init__
( self, host: str = "localhost", port: int = logging.handlers.DEFAULT_TCP_LOGGING_PORT
autosklearn/util/logging_.py:332
Method__init__
(self, result: typing.Any)
autosklearn/util/single_thread_client.py:15
Method__init__
(self)
autosklearn/util/single_thread_client.py:40
Method__init__
(*args, **kwargs)
test/test_pipeline/test_classification.py:93
Method__init__
(self, feat_type: Optional[FEAT_TYPE_TYPE] = None)
test/test_pipeline/test_base.py:16
Method__init__
(self, logfile: str)
test/test_automl/automl_utils.py:110
Method__init__
(self, name, value)
test/test_metalearning/test_metalearning.py:15
Method__init__
( self, name: Optional[str] = None, host: Optional[str] = None, port: Optional
test/mocks/logging.py:22
Method__init__
(self)
test/test_evaluation/test_train_evaluator.py:75
Method__init__
(self)
test/test_evaluation/test_train_evaluator.py:91
Method__init__
(self)
test/test_evaluation/test_train_evaluator.py:201
Method__init__
(self)
test/test_evaluation/test_train_evaluator.py:260
Method__init__
(self)
test/test_evaluation/test_train_evaluator.py:2837
Method__init__
(self, methodName)
test/test_evaluation/evaluation_util.py:74
Method__init__
(self)
test/test_evaluation/test_test_evaluator.py:90
Method__init__
(self, *args, **kwargs)
test/test_ensemble_builder/test_ensemble_builder.py:913
Method__init__
(self, fname)
test/test_util/test_trials_callback.py:17
Method__init__
(self)
test/test_util/test_backend.py:12
Method__init__
Parameters ---------- key : str The key of the item stored cache_dir : Path The dir where th
test/fixtures/caching.py:66
Method__init__
(self)
test/fixtures/automl.py:89
Method__init__
(self, x)
test/test_data/test_feature_validator.py:515
Method__init__
(self, info, feat_type=None)
scripts/02_retrieve_metadata.py:193
Method__init__
This preprocessors does not change the data
examples/80_extending/example_extending_data_preprocessor.py:27
Method__init__
(self, solver, tol, shrinkage=None, random_state=None)
examples/80_extending/example_extending_preprocessor.py:37
Method__init__
(self, alpha, kernel, gamma, degree, coef0, random_state=None)
examples/80_extending/example_extending_regression.py:44
Method__init__
( self, hidden_layer_depth, num_nodes_per_layer, activation, alpha,
examples/80_extending/example_extending_classification.py:42
Method__init__
(self, n_estimators, max_features, random_state=None)
examples/80_extending/example_restrict_number_of_hyperparameters.py:40
Method__iter__
(self)
autosklearn/metalearning/metafeatures/metafeatures.py:83
Method__iter__
(self)
autosklearn/util/stopwatch.py:87
Method__iter__
(cls)
autosklearn/util/data.py:178
Method__len__
(self)
autosklearn/util/stopwatch.py:84
Method__len__
(cls)
autosklearn/util/data.py:182
Method__repr__
(self)
autosklearn/metrics/__init__.py:57
Method__repr__
(self)
autosklearn/metalearning/metafeatures/metafeature.py:85
Method__repr__
(self, verbosity=0)
autosklearn/metalearning/metafeatures/metafeature.py:151
Method__repr__
(self)
autosklearn/metalearning/metalearning/meta_base.py:18
Method__repr__
(self)
autosklearn/data/abstract_data_manager.py:49
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