1671 lines
37 KiB
ReStructuredText
1671 lines
37 KiB
ReStructuredText
.. _api_ref:
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=============
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API Reference
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=============
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This is the class and function reference of scikit-learn. Please refer to
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the :ref:`full user guide <user_guide>` for further details, as the class and
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function raw specifications may not be enough to give full guidelines on their
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uses.
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For reference on concepts repeated across the API, see :ref:`glossary`.
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:mod:`sklearn.base`: Base classes and utility functions
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=======================================================
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.. automodule:: sklearn.base
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:no-members:
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:no-inherited-members:
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Base classes
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------------
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.. currentmodule:: sklearn
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.. autosummary::
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:nosignatures:
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:toctree: generated/
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:template: class.rst
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base.BaseEstimator
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base.BiclusterMixin
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base.ClassifierMixin
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base.ClusterMixin
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base.DensityMixin
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base.RegressorMixin
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base.TransformerMixin
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feature_selection.SelectorMixin
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Functions
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---------
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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base.clone
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base.is_classifier
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base.is_regressor
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config_context
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get_config
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set_config
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show_versions
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.. _calibration_ref:
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:mod:`sklearn.calibration`: Probability Calibration
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===================================================
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.. automodule:: sklearn.calibration
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`calibration` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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calibration.CalibratedClassifierCV
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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calibration.calibration_curve
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.. _cluster_ref:
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:mod:`sklearn.cluster`: Clustering
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==================================
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.. automodule:: sklearn.cluster
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`clustering` and :ref:`biclustering` sections for
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further details.
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Classes
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-------
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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cluster.AffinityPropagation
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cluster.AgglomerativeClustering
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cluster.Birch
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cluster.DBSCAN
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cluster.FeatureAgglomeration
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cluster.KMeans
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cluster.MiniBatchKMeans
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cluster.MeanShift
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cluster.OPTICS
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cluster.SpectralClustering
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cluster.SpectralBiclustering
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cluster.SpectralCoclustering
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Functions
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---------
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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cluster.affinity_propagation
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cluster.cluster_optics_dbscan
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cluster.cluster_optics_xi
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cluster.compute_optics_graph
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cluster.dbscan
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cluster.estimate_bandwidth
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cluster.k_means
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cluster.kmeans_plusplus
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cluster.mean_shift
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cluster.spectral_clustering
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cluster.ward_tree
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.. _compose_ref:
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:mod:`sklearn.compose`: Composite Estimators
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============================================
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.. automodule:: sklearn.compose
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`combining_estimators` section for further
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details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated
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:template: class.rst
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compose.ColumnTransformer
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compose.TransformedTargetRegressor
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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compose.make_column_transformer
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compose.make_column_selector
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.. _covariance_ref:
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:mod:`sklearn.covariance`: Covariance Estimators
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================================================
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.. automodule:: sklearn.covariance
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`covariance` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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covariance.EmpiricalCovariance
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covariance.EllipticEnvelope
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covariance.GraphicalLasso
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covariance.GraphicalLassoCV
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covariance.LedoitWolf
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covariance.MinCovDet
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covariance.OAS
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covariance.ShrunkCovariance
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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covariance.empirical_covariance
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covariance.graphical_lasso
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covariance.ledoit_wolf
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covariance.oas
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covariance.shrunk_covariance
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.. _cross_decomposition_ref:
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:mod:`sklearn.cross_decomposition`: Cross decomposition
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=======================================================
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.. automodule:: sklearn.cross_decomposition
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`cross_decomposition` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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cross_decomposition.CCA
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cross_decomposition.PLSCanonical
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cross_decomposition.PLSRegression
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cross_decomposition.PLSSVD
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.. _datasets_ref:
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:mod:`sklearn.datasets`: Datasets
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=================================
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.. automodule:: sklearn.datasets
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`datasets` section for further details.
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Loaders
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-------
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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datasets.clear_data_home
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datasets.dump_svmlight_file
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datasets.fetch_20newsgroups
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datasets.fetch_20newsgroups_vectorized
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datasets.fetch_california_housing
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datasets.fetch_covtype
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datasets.fetch_kddcup99
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datasets.fetch_lfw_pairs
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datasets.fetch_lfw_people
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datasets.fetch_olivetti_faces
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datasets.fetch_openml
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datasets.fetch_rcv1
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datasets.fetch_species_distributions
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datasets.get_data_home
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datasets.load_boston
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datasets.load_breast_cancer
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datasets.load_diabetes
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datasets.load_digits
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datasets.load_files
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datasets.load_iris
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datasets.load_linnerud
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datasets.load_sample_image
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datasets.load_sample_images
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datasets.load_svmlight_file
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datasets.load_svmlight_files
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datasets.load_wine
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Samples generator
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-----------------
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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datasets.make_biclusters
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datasets.make_blobs
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datasets.make_checkerboard
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datasets.make_circles
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datasets.make_classification
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datasets.make_friedman1
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datasets.make_friedman2
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datasets.make_friedman3
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datasets.make_gaussian_quantiles
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datasets.make_hastie_10_2
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datasets.make_low_rank_matrix
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datasets.make_moons
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datasets.make_multilabel_classification
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datasets.make_regression
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datasets.make_s_curve
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datasets.make_sparse_coded_signal
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datasets.make_sparse_spd_matrix
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datasets.make_sparse_uncorrelated
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datasets.make_spd_matrix
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datasets.make_swiss_roll
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.. _decomposition_ref:
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:mod:`sklearn.decomposition`: Matrix Decomposition
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==================================================
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.. automodule:: sklearn.decomposition
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`decompositions` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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decomposition.DictionaryLearning
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decomposition.FactorAnalysis
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decomposition.FastICA
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decomposition.IncrementalPCA
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decomposition.KernelPCA
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decomposition.LatentDirichletAllocation
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decomposition.MiniBatchDictionaryLearning
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decomposition.MiniBatchSparsePCA
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decomposition.NMF
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decomposition.PCA
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decomposition.SparsePCA
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decomposition.SparseCoder
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decomposition.TruncatedSVD
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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decomposition.dict_learning
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decomposition.dict_learning_online
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decomposition.fastica
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decomposition.non_negative_factorization
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decomposition.sparse_encode
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.. _lda_ref:
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:mod:`sklearn.discriminant_analysis`: Discriminant Analysis
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===========================================================
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.. automodule:: sklearn.discriminant_analysis
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`lda_qda` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated
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:template: class.rst
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discriminant_analysis.LinearDiscriminantAnalysis
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discriminant_analysis.QuadraticDiscriminantAnalysis
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.. _dummy_ref:
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:mod:`sklearn.dummy`: Dummy estimators
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======================================
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.. automodule:: sklearn.dummy
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`model_evaluation` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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dummy.DummyClassifier
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dummy.DummyRegressor
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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.. _ensemble_ref:
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:mod:`sklearn.ensemble`: Ensemble Methods
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=========================================
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.. automodule:: sklearn.ensemble
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`ensemble` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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ensemble.AdaBoostClassifier
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ensemble.AdaBoostRegressor
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ensemble.BaggingClassifier
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ensemble.BaggingRegressor
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ensemble.ExtraTreesClassifier
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ensemble.ExtraTreesRegressor
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ensemble.GradientBoostingClassifier
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ensemble.GradientBoostingRegressor
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ensemble.IsolationForest
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ensemble.RandomForestClassifier
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ensemble.RandomForestRegressor
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ensemble.RandomTreesEmbedding
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ensemble.StackingClassifier
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ensemble.StackingRegressor
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ensemble.VotingClassifier
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ensemble.VotingRegressor
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ensemble.HistGradientBoostingRegressor
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ensemble.HistGradientBoostingClassifier
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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.. _exceptions_ref:
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:mod:`sklearn.exceptions`: Exceptions and warnings
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==================================================
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.. automodule:: sklearn.exceptions
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:no-members:
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:no-inherited-members:
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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exceptions.ConvergenceWarning
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exceptions.DataConversionWarning
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exceptions.DataDimensionalityWarning
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exceptions.EfficiencyWarning
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exceptions.FitFailedWarning
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exceptions.NotFittedError
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exceptions.UndefinedMetricWarning
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:mod:`sklearn.experimental`: Experimental
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=========================================
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.. automodule:: sklearn.experimental
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:no-members:
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:no-inherited-members:
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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experimental.enable_hist_gradient_boosting
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experimental.enable_iterative_imputer
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experimental.enable_halving_search_cv
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.. _feature_extraction_ref:
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:mod:`sklearn.feature_extraction`: Feature Extraction
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=====================================================
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.. automodule:: sklearn.feature_extraction
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`feature_extraction` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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feature_extraction.DictVectorizer
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feature_extraction.FeatureHasher
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From images
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-----------
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.. automodule:: sklearn.feature_extraction.image
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:no-members:
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:no-inherited-members:
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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feature_extraction.image.extract_patches_2d
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feature_extraction.image.grid_to_graph
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feature_extraction.image.img_to_graph
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feature_extraction.image.reconstruct_from_patches_2d
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:template: class.rst
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feature_extraction.image.PatchExtractor
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.. _text_feature_extraction_ref:
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From text
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---------
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.. automodule:: sklearn.feature_extraction.text
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:no-members:
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:no-inherited-members:
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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feature_extraction.text.CountVectorizer
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feature_extraction.text.HashingVectorizer
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feature_extraction.text.TfidfTransformer
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feature_extraction.text.TfidfVectorizer
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.. _feature_selection_ref:
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:mod:`sklearn.feature_selection`: Feature Selection
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===================================================
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.. automodule:: sklearn.feature_selection
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`feature_selection` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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feature_selection.GenericUnivariateSelect
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feature_selection.SelectPercentile
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feature_selection.SelectKBest
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feature_selection.SelectFpr
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feature_selection.SelectFdr
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feature_selection.SelectFromModel
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feature_selection.SelectFwe
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feature_selection.SequentialFeatureSelector
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feature_selection.RFE
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feature_selection.RFECV
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feature_selection.VarianceThreshold
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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feature_selection.chi2
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feature_selection.f_classif
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feature_selection.f_regression
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feature_selection.r_regression
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feature_selection.mutual_info_classif
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feature_selection.mutual_info_regression
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.. _gaussian_process_ref:
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:mod:`sklearn.gaussian_process`: Gaussian Processes
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===================================================
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.. automodule:: sklearn.gaussian_process
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`gaussian_process` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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gaussian_process.GaussianProcessClassifier
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gaussian_process.GaussianProcessRegressor
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Kernels:
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.. autosummary::
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:toctree: generated/
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:template: class_with_call.rst
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gaussian_process.kernels.CompoundKernel
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gaussian_process.kernels.ConstantKernel
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gaussian_process.kernels.DotProduct
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gaussian_process.kernels.ExpSineSquared
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gaussian_process.kernels.Exponentiation
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gaussian_process.kernels.Hyperparameter
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gaussian_process.kernels.Kernel
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gaussian_process.kernels.Matern
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gaussian_process.kernels.PairwiseKernel
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gaussian_process.kernels.Product
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gaussian_process.kernels.RBF
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gaussian_process.kernels.RationalQuadratic
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gaussian_process.kernels.Sum
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gaussian_process.kernels.WhiteKernel
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.. _impute_ref:
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:mod:`sklearn.impute`: Impute
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=============================
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.. automodule:: sklearn.impute
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:no-members:
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:no-inherited-members:
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**User guide:** See the :ref:`Impute` section for further details.
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.. currentmodule:: sklearn
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.. autosummary::
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:toctree: generated/
|
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:template: class.rst
|
|
|
|
impute.SimpleImputer
|
|
impute.IterativeImputer
|
|
impute.MissingIndicator
|
|
impute.KNNImputer
|
|
|
|
|
|
.. _inspection_ref:
|
|
|
|
:mod:`sklearn.inspection`: Inspection
|
|
=====================================
|
|
|
|
.. automodule:: sklearn.inspection
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
inspection.partial_dependence
|
|
inspection.permutation_importance
|
|
|
|
Plotting
|
|
--------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
inspection.DecisionBoundaryDisplay
|
|
inspection.PartialDependenceDisplay
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
inspection.plot_partial_dependence
|
|
|
|
.. _isotonic_ref:
|
|
|
|
:mod:`sklearn.isotonic`: Isotonic regression
|
|
============================================
|
|
|
|
.. automodule:: sklearn.isotonic
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`isotonic` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
isotonic.IsotonicRegression
|
|
|
|
.. autosummary::
|
|
:toctree: generated
|
|
:template: function.rst
|
|
|
|
isotonic.check_increasing
|
|
isotonic.isotonic_regression
|
|
|
|
|
|
.. _kernel_approximation_ref:
|
|
|
|
:mod:`sklearn.kernel_approximation`: Kernel Approximation
|
|
=========================================================
|
|
|
|
.. automodule:: sklearn.kernel_approximation
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`kernel_approximation` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
kernel_approximation.AdditiveChi2Sampler
|
|
kernel_approximation.Nystroem
|
|
kernel_approximation.PolynomialCountSketch
|
|
kernel_approximation.RBFSampler
|
|
kernel_approximation.SkewedChi2Sampler
|
|
|
|
.. _kernel_ridge_ref:
|
|
|
|
:mod:`sklearn.kernel_ridge`: Kernel Ridge Regression
|
|
====================================================
|
|
|
|
.. automodule:: sklearn.kernel_ridge
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`kernel_ridge` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
kernel_ridge.KernelRidge
|
|
|
|
.. _linear_model_ref:
|
|
|
|
:mod:`sklearn.linear_model`: Linear Models
|
|
==========================================
|
|
|
|
.. automodule:: sklearn.linear_model
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`linear_model` section for further details.
|
|
|
|
The following subsections are only rough guidelines: the same estimator can
|
|
fall into multiple categories, depending on its parameters.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
Linear classifiers
|
|
------------------
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
linear_model.LogisticRegression
|
|
linear_model.LogisticRegressionCV
|
|
linear_model.PassiveAggressiveClassifier
|
|
linear_model.Perceptron
|
|
linear_model.RidgeClassifier
|
|
linear_model.RidgeClassifierCV
|
|
linear_model.SGDClassifier
|
|
linear_model.SGDOneClassSVM
|
|
|
|
Classical linear regressors
|
|
---------------------------
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
linear_model.LinearRegression
|
|
linear_model.Ridge
|
|
linear_model.RidgeCV
|
|
linear_model.SGDRegressor
|
|
|
|
Regressors with variable selection
|
|
----------------------------------
|
|
|
|
The following estimators have built-in variable selection fitting
|
|
procedures, but any estimator using a L1 or elastic-net penalty also
|
|
performs variable selection: typically :class:`~linear_model.SGDRegressor`
|
|
or :class:`~sklearn.linear_model.SGDClassifier` with an appropriate penalty.
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
linear_model.ElasticNet
|
|
linear_model.ElasticNetCV
|
|
linear_model.Lars
|
|
linear_model.LarsCV
|
|
linear_model.Lasso
|
|
linear_model.LassoCV
|
|
linear_model.LassoLars
|
|
linear_model.LassoLarsCV
|
|
linear_model.LassoLarsIC
|
|
linear_model.OrthogonalMatchingPursuit
|
|
linear_model.OrthogonalMatchingPursuitCV
|
|
|
|
Bayesian regressors
|
|
-------------------
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
linear_model.ARDRegression
|
|
linear_model.BayesianRidge
|
|
|
|
Multi-task linear regressors with variable selection
|
|
----------------------------------------------------
|
|
|
|
These estimators fit multiple regression problems (or tasks) jointly, while
|
|
inducing sparse coefficients. While the inferred coefficients may differ
|
|
between the tasks, they are constrained to agree on the features that are
|
|
selected (non-zero coefficients).
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
linear_model.MultiTaskElasticNet
|
|
linear_model.MultiTaskElasticNetCV
|
|
linear_model.MultiTaskLasso
|
|
linear_model.MultiTaskLassoCV
|
|
|
|
Outlier-robust regressors
|
|
-------------------------
|
|
|
|
Any estimator using the Huber loss would also be robust to outliers, e.g.
|
|
:class:`~linear_model.SGDRegressor` with ``loss='huber'``.
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
linear_model.HuberRegressor
|
|
linear_model.QuantileRegressor
|
|
linear_model.RANSACRegressor
|
|
linear_model.TheilSenRegressor
|
|
|
|
Generalized linear models (GLM) for regression
|
|
----------------------------------------------
|
|
|
|
These models allow for response variables to have error distributions other
|
|
than a normal distribution:
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
linear_model.PoissonRegressor
|
|
linear_model.TweedieRegressor
|
|
linear_model.GammaRegressor
|
|
|
|
|
|
Miscellaneous
|
|
-------------
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
linear_model.PassiveAggressiveRegressor
|
|
linear_model.enet_path
|
|
linear_model.lars_path
|
|
linear_model.lars_path_gram
|
|
linear_model.lasso_path
|
|
linear_model.orthogonal_mp
|
|
linear_model.orthogonal_mp_gram
|
|
linear_model.ridge_regression
|
|
|
|
|
|
.. _manifold_ref:
|
|
|
|
:mod:`sklearn.manifold`: Manifold Learning
|
|
==========================================
|
|
|
|
.. automodule:: sklearn.manifold
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`manifold` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated
|
|
:template: class.rst
|
|
|
|
manifold.Isomap
|
|
manifold.LocallyLinearEmbedding
|
|
manifold.MDS
|
|
manifold.SpectralEmbedding
|
|
manifold.TSNE
|
|
|
|
.. autosummary::
|
|
:toctree: generated
|
|
:template: function.rst
|
|
|
|
manifold.locally_linear_embedding
|
|
manifold.smacof
|
|
manifold.spectral_embedding
|
|
manifold.trustworthiness
|
|
|
|
|
|
.. _metrics_ref:
|
|
|
|
:mod:`sklearn.metrics`: Metrics
|
|
===============================
|
|
|
|
See the :ref:`model_evaluation` section and the :ref:`metrics` section of the
|
|
user guide for further details.
|
|
|
|
.. automodule:: sklearn.metrics
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
Model Selection Interface
|
|
-------------------------
|
|
See the :ref:`scoring_parameter` section of the user guide for further
|
|
details.
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.check_scoring
|
|
metrics.get_scorer
|
|
metrics.get_scorer_names
|
|
metrics.make_scorer
|
|
|
|
Classification metrics
|
|
----------------------
|
|
|
|
See the :ref:`classification_metrics` section of the user guide for further
|
|
details.
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.accuracy_score
|
|
metrics.auc
|
|
metrics.average_precision_score
|
|
metrics.balanced_accuracy_score
|
|
metrics.brier_score_loss
|
|
metrics.classification_report
|
|
metrics.cohen_kappa_score
|
|
metrics.confusion_matrix
|
|
metrics.dcg_score
|
|
metrics.det_curve
|
|
metrics.f1_score
|
|
metrics.fbeta_score
|
|
metrics.hamming_loss
|
|
metrics.hinge_loss
|
|
metrics.jaccard_score
|
|
metrics.log_loss
|
|
metrics.matthews_corrcoef
|
|
metrics.multilabel_confusion_matrix
|
|
metrics.ndcg_score
|
|
metrics.precision_recall_curve
|
|
metrics.precision_recall_fscore_support
|
|
metrics.precision_score
|
|
metrics.recall_score
|
|
metrics.roc_auc_score
|
|
metrics.roc_curve
|
|
metrics.top_k_accuracy_score
|
|
metrics.zero_one_loss
|
|
|
|
Regression metrics
|
|
------------------
|
|
|
|
See the :ref:`regression_metrics` section of the user guide for further
|
|
details.
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.explained_variance_score
|
|
metrics.max_error
|
|
metrics.mean_absolute_error
|
|
metrics.mean_squared_error
|
|
metrics.mean_squared_log_error
|
|
metrics.median_absolute_error
|
|
metrics.mean_absolute_percentage_error
|
|
metrics.r2_score
|
|
metrics.mean_poisson_deviance
|
|
metrics.mean_gamma_deviance
|
|
metrics.mean_tweedie_deviance
|
|
metrics.d2_tweedie_score
|
|
metrics.mean_pinball_loss
|
|
|
|
Multilabel ranking metrics
|
|
--------------------------
|
|
See the :ref:`multilabel_ranking_metrics` section of the user guide for further
|
|
details.
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.coverage_error
|
|
metrics.label_ranking_average_precision_score
|
|
metrics.label_ranking_loss
|
|
|
|
|
|
Clustering metrics
|
|
------------------
|
|
|
|
See the :ref:`clustering_evaluation` section of the user guide for further
|
|
details.
|
|
|
|
.. automodule:: sklearn.metrics.cluster
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.adjusted_mutual_info_score
|
|
metrics.adjusted_rand_score
|
|
metrics.calinski_harabasz_score
|
|
metrics.davies_bouldin_score
|
|
metrics.completeness_score
|
|
metrics.cluster.contingency_matrix
|
|
metrics.cluster.pair_confusion_matrix
|
|
metrics.fowlkes_mallows_score
|
|
metrics.homogeneity_completeness_v_measure
|
|
metrics.homogeneity_score
|
|
metrics.mutual_info_score
|
|
metrics.normalized_mutual_info_score
|
|
metrics.rand_score
|
|
metrics.silhouette_score
|
|
metrics.silhouette_samples
|
|
metrics.v_measure_score
|
|
|
|
Biclustering metrics
|
|
--------------------
|
|
|
|
See the :ref:`biclustering_evaluation` section of the user guide for
|
|
further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.consensus_score
|
|
|
|
Distance metrics
|
|
----------------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
metrics.DistanceMetric
|
|
|
|
Pairwise metrics
|
|
----------------
|
|
|
|
See the :ref:`metrics` section of the user guide for further details.
|
|
|
|
.. automodule:: sklearn.metrics.pairwise
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.pairwise.additive_chi2_kernel
|
|
metrics.pairwise.chi2_kernel
|
|
metrics.pairwise.cosine_similarity
|
|
metrics.pairwise.cosine_distances
|
|
metrics.pairwise.distance_metrics
|
|
metrics.pairwise.euclidean_distances
|
|
metrics.pairwise.haversine_distances
|
|
metrics.pairwise.kernel_metrics
|
|
metrics.pairwise.laplacian_kernel
|
|
metrics.pairwise.linear_kernel
|
|
metrics.pairwise.manhattan_distances
|
|
metrics.pairwise.nan_euclidean_distances
|
|
metrics.pairwise.pairwise_kernels
|
|
metrics.pairwise.polynomial_kernel
|
|
metrics.pairwise.rbf_kernel
|
|
metrics.pairwise.sigmoid_kernel
|
|
metrics.pairwise.paired_euclidean_distances
|
|
metrics.pairwise.paired_manhattan_distances
|
|
metrics.pairwise.paired_cosine_distances
|
|
metrics.pairwise.paired_distances
|
|
metrics.pairwise_distances
|
|
metrics.pairwise_distances_argmin
|
|
metrics.pairwise_distances_argmin_min
|
|
metrics.pairwise_distances_chunked
|
|
|
|
|
|
Plotting
|
|
--------
|
|
|
|
See the :ref:`visualizations` section of the user guide for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
metrics.plot_confusion_matrix
|
|
metrics.plot_det_curve
|
|
metrics.plot_precision_recall_curve
|
|
metrics.plot_roc_curve
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
metrics.ConfusionMatrixDisplay
|
|
metrics.DetCurveDisplay
|
|
metrics.PrecisionRecallDisplay
|
|
metrics.RocCurveDisplay
|
|
calibration.CalibrationDisplay
|
|
|
|
.. _mixture_ref:
|
|
|
|
:mod:`sklearn.mixture`: Gaussian Mixture Models
|
|
===============================================
|
|
|
|
.. automodule:: sklearn.mixture
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`mixture` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
mixture.BayesianGaussianMixture
|
|
mixture.GaussianMixture
|
|
|
|
.. _modelselection_ref:
|
|
|
|
:mod:`sklearn.model_selection`: Model Selection
|
|
===============================================
|
|
|
|
.. automodule:: sklearn.model_selection
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`cross_validation`, :ref:`grid_search` and
|
|
:ref:`learning_curve` sections for further details.
|
|
|
|
Splitter Classes
|
|
----------------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
model_selection.GroupKFold
|
|
model_selection.GroupShuffleSplit
|
|
model_selection.KFold
|
|
model_selection.LeaveOneGroupOut
|
|
model_selection.LeavePGroupsOut
|
|
model_selection.LeaveOneOut
|
|
model_selection.LeavePOut
|
|
model_selection.PredefinedSplit
|
|
model_selection.RepeatedKFold
|
|
model_selection.RepeatedStratifiedKFold
|
|
model_selection.ShuffleSplit
|
|
model_selection.StratifiedKFold
|
|
model_selection.StratifiedShuffleSplit
|
|
model_selection.StratifiedGroupKFold
|
|
model_selection.TimeSeriesSplit
|
|
|
|
Splitter Functions
|
|
------------------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
model_selection.check_cv
|
|
model_selection.train_test_split
|
|
|
|
.. _hyper_parameter_optimizers:
|
|
|
|
Hyper-parameter optimizers
|
|
--------------------------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
model_selection.GridSearchCV
|
|
model_selection.HalvingGridSearchCV
|
|
model_selection.ParameterGrid
|
|
model_selection.ParameterSampler
|
|
model_selection.RandomizedSearchCV
|
|
model_selection.HalvingRandomSearchCV
|
|
|
|
|
|
Model validation
|
|
----------------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
model_selection.cross_validate
|
|
model_selection.cross_val_predict
|
|
model_selection.cross_val_score
|
|
model_selection.learning_curve
|
|
model_selection.permutation_test_score
|
|
model_selection.validation_curve
|
|
|
|
.. _multiclass_ref:
|
|
|
|
:mod:`sklearn.multiclass`: Multiclass classification
|
|
====================================================
|
|
|
|
.. automodule:: sklearn.multiclass
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`multiclass_classification` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated
|
|
:template: class.rst
|
|
|
|
multiclass.OneVsRestClassifier
|
|
multiclass.OneVsOneClassifier
|
|
multiclass.OutputCodeClassifier
|
|
|
|
.. _multioutput_ref:
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|
|
|
:mod:`sklearn.multioutput`: Multioutput regression and classification
|
|
=====================================================================
|
|
|
|
.. automodule:: sklearn.multioutput
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`multilabel_classification`,
|
|
:ref:`multiclass_multioutput_classification`, and
|
|
:ref:`multioutput_regression` sections for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated
|
|
:template: class.rst
|
|
|
|
multioutput.ClassifierChain
|
|
multioutput.MultiOutputRegressor
|
|
multioutput.MultiOutputClassifier
|
|
multioutput.RegressorChain
|
|
|
|
.. _naive_bayes_ref:
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|
|
|
:mod:`sklearn.naive_bayes`: Naive Bayes
|
|
=======================================
|
|
|
|
.. automodule:: sklearn.naive_bayes
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`naive_bayes` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
naive_bayes.BernoulliNB
|
|
naive_bayes.CategoricalNB
|
|
naive_bayes.ComplementNB
|
|
naive_bayes.GaussianNB
|
|
naive_bayes.MultinomialNB
|
|
|
|
|
|
.. _neighbors_ref:
|
|
|
|
:mod:`sklearn.neighbors`: Nearest Neighbors
|
|
===========================================
|
|
|
|
.. automodule:: sklearn.neighbors
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`neighbors` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
neighbors.BallTree
|
|
neighbors.KDTree
|
|
neighbors.KernelDensity
|
|
neighbors.KNeighborsClassifier
|
|
neighbors.KNeighborsRegressor
|
|
neighbors.KNeighborsTransformer
|
|
neighbors.LocalOutlierFactor
|
|
neighbors.RadiusNeighborsClassifier
|
|
neighbors.RadiusNeighborsRegressor
|
|
neighbors.RadiusNeighborsTransformer
|
|
neighbors.NearestCentroid
|
|
neighbors.NearestNeighbors
|
|
neighbors.NeighborhoodComponentsAnalysis
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
neighbors.kneighbors_graph
|
|
neighbors.radius_neighbors_graph
|
|
|
|
.. _neural_network_ref:
|
|
|
|
:mod:`sklearn.neural_network`: Neural network models
|
|
====================================================
|
|
|
|
.. automodule:: sklearn.neural_network
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`neural_networks_supervised` and :ref:`neural_networks_unsupervised` sections for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
neural_network.BernoulliRBM
|
|
neural_network.MLPClassifier
|
|
neural_network.MLPRegressor
|
|
|
|
.. _pipeline_ref:
|
|
|
|
:mod:`sklearn.pipeline`: Pipeline
|
|
=================================
|
|
|
|
.. automodule:: sklearn.pipeline
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`combining_estimators` section for further
|
|
details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
pipeline.FeatureUnion
|
|
pipeline.Pipeline
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
pipeline.make_pipeline
|
|
pipeline.make_union
|
|
|
|
.. _preprocessing_ref:
|
|
|
|
:mod:`sklearn.preprocessing`: Preprocessing and Normalization
|
|
=============================================================
|
|
|
|
.. automodule:: sklearn.preprocessing
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`preprocessing` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
preprocessing.Binarizer
|
|
preprocessing.FunctionTransformer
|
|
preprocessing.KBinsDiscretizer
|
|
preprocessing.KernelCenterer
|
|
preprocessing.LabelBinarizer
|
|
preprocessing.LabelEncoder
|
|
preprocessing.MultiLabelBinarizer
|
|
preprocessing.MaxAbsScaler
|
|
preprocessing.MinMaxScaler
|
|
preprocessing.Normalizer
|
|
preprocessing.OneHotEncoder
|
|
preprocessing.OrdinalEncoder
|
|
preprocessing.PolynomialFeatures
|
|
preprocessing.PowerTransformer
|
|
preprocessing.QuantileTransformer
|
|
preprocessing.RobustScaler
|
|
preprocessing.SplineTransformer
|
|
preprocessing.StandardScaler
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
preprocessing.add_dummy_feature
|
|
preprocessing.binarize
|
|
preprocessing.label_binarize
|
|
preprocessing.maxabs_scale
|
|
preprocessing.minmax_scale
|
|
preprocessing.normalize
|
|
preprocessing.quantile_transform
|
|
preprocessing.robust_scale
|
|
preprocessing.scale
|
|
preprocessing.power_transform
|
|
|
|
|
|
.. _random_projection_ref:
|
|
|
|
:mod:`sklearn.random_projection`: Random projection
|
|
===================================================
|
|
|
|
.. automodule:: sklearn.random_projection
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`random_projection` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
random_projection.GaussianRandomProjection
|
|
random_projection.SparseRandomProjection
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
random_projection.johnson_lindenstrauss_min_dim
|
|
|
|
|
|
.. _semi_supervised_ref:
|
|
|
|
:mod:`sklearn.semi_supervised`: Semi-Supervised Learning
|
|
========================================================
|
|
|
|
.. automodule:: sklearn.semi_supervised
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`semi_supervised` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
semi_supervised.LabelPropagation
|
|
semi_supervised.LabelSpreading
|
|
semi_supervised.SelfTrainingClassifier
|
|
|
|
|
|
.. _svm_ref:
|
|
|
|
:mod:`sklearn.svm`: Support Vector Machines
|
|
===========================================
|
|
|
|
.. automodule:: sklearn.svm
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`svm` section for further details.
|
|
|
|
Estimators
|
|
----------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
svm.LinearSVC
|
|
svm.LinearSVR
|
|
svm.NuSVC
|
|
svm.NuSVR
|
|
svm.OneClassSVM
|
|
svm.SVC
|
|
svm.SVR
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
svm.l1_min_c
|
|
|
|
.. _tree_ref:
|
|
|
|
:mod:`sklearn.tree`: Decision Trees
|
|
===================================
|
|
|
|
.. automodule:: sklearn.tree
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**User guide:** See the :ref:`tree` section for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
tree.DecisionTreeClassifier
|
|
tree.DecisionTreeRegressor
|
|
tree.ExtraTreeClassifier
|
|
tree.ExtraTreeRegressor
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
tree.export_graphviz
|
|
tree.export_text
|
|
|
|
Plotting
|
|
--------
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
tree.plot_tree
|
|
|
|
.. _utils_ref:
|
|
|
|
:mod:`sklearn.utils`: Utilities
|
|
===============================
|
|
|
|
.. automodule:: sklearn.utils
|
|
:no-members:
|
|
:no-inherited-members:
|
|
|
|
**Developer guide:** See the :ref:`developers-utils` page for further details.
|
|
|
|
.. currentmodule:: sklearn
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: class.rst
|
|
|
|
utils.Bunch
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
utils.arrayfuncs.min_pos
|
|
utils.as_float_array
|
|
utils.assert_all_finite
|
|
utils.check_X_y
|
|
utils.check_array
|
|
utils.check_scalar
|
|
utils.check_consistent_length
|
|
utils.check_random_state
|
|
utils.class_weight.compute_class_weight
|
|
utils.class_weight.compute_sample_weight
|
|
utils.deprecated
|
|
utils.estimator_checks.check_estimator
|
|
utils.estimator_checks.parametrize_with_checks
|
|
utils.estimator_html_repr
|
|
utils.extmath.safe_sparse_dot
|
|
utils.extmath.randomized_range_finder
|
|
utils.extmath.randomized_svd
|
|
utils.extmath.fast_logdet
|
|
utils.extmath.density
|
|
utils.extmath.weighted_mode
|
|
utils.gen_batches
|
|
utils.gen_even_slices
|
|
utils.graph.single_source_shortest_path_length
|
|
utils.indexable
|
|
utils.metaestimators.available_if
|
|
utils.multiclass.type_of_target
|
|
utils.multiclass.is_multilabel
|
|
utils.multiclass.unique_labels
|
|
utils.murmurhash3_32
|
|
utils.resample
|
|
utils._safe_indexing
|
|
utils.safe_mask
|
|
utils.safe_sqr
|
|
utils.shuffle
|
|
utils.sparsefuncs.incr_mean_variance_axis
|
|
utils.sparsefuncs.inplace_column_scale
|
|
utils.sparsefuncs.inplace_row_scale
|
|
utils.sparsefuncs.inplace_swap_row
|
|
utils.sparsefuncs.inplace_swap_column
|
|
utils.sparsefuncs.mean_variance_axis
|
|
utils.sparsefuncs.inplace_csr_column_scale
|
|
utils.sparsefuncs_fast.inplace_csr_row_normalize_l1
|
|
utils.sparsefuncs_fast.inplace_csr_row_normalize_l2
|
|
utils.random.sample_without_replacement
|
|
utils.validation.check_is_fitted
|
|
utils.validation.check_memory
|
|
utils.validation.check_symmetric
|
|
utils.validation.column_or_1d
|
|
utils.validation.has_fit_parameter
|
|
utils.all_estimators
|
|
|
|
Utilities from joblib:
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
utils.parallel_backend
|
|
utils.register_parallel_backend
|
|
|
|
|
|
Recently deprecated
|
|
===================
|
|
|
|
To be removed in 1.3
|
|
--------------------
|
|
|
|
.. autosummary::
|
|
:toctree: generated/
|
|
:template: function.rst
|
|
|
|
utils.metaestimators.if_delegate_has_method
|