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‎.gitignore‎

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# files generated from a template
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sklearn/utils/_seq_dataset.pyx
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sklearn/utils/_seq_dataset.pxd
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sklearn/linear_model/sag_fast.pyx
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sklearn/linear_model/_sag_fast.pyx
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# deprecated paths
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# TODO: Remove in 0.24
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sklearn/svm/libsvm_sparse.py
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sklearn/svm/liblinear.py
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sklearn/linear_model/base.py
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sklearn/linear_model/bayes.py
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sklearn/linear_model/cd_fast.py
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sklearn/linear_model/coordinate_descent.py
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sklearn/linear_model/huber.py
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sklearn/linear_model/least_angle.py
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sklearn/linear_model/logistic.py
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sklearn/linear_model/omp.py
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sklearn/linear_model/passive_aggressive.py
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sklearn/linear_model/perceptron.py
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sklearn/linear_model/ransac.py
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sklearn/linear_model/ridge.py
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sklearn/linear_model/sag.py
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sklearn/linear_model/sag_fast.py
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sklearn/linear_model/sgd_fast.py
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sklearn/linear_model/stochastic_gradient.py
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sklearn/linear_model/theil_sen.py
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sklearn/metrics/cluster/bicluster.py
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sklearn/metrics/cluster/supervised.py
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sklearn/metrics/cluster/unsupervised.py
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sklearn/metrics/cluster/expected_mutual_info_fast.py
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sklearn/metrics/base.py
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sklearn/metrics/classification.py
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sklearn/metrics/regression.py
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sklearn/metrics/ranking.py
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sklearn/metrics/pairwise_fast.py
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sklearn/metrics/scorer.py
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sklearn/inspection/partial_dependence.py
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sklearn/inspection/permutation_importance.py
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‎benchmarks/bench_rcv1_logreg_convergence.py‎

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from sklearn.linear_model import (LogisticRegression, SGDClassifier)
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from sklearn.datasets import fetch_rcv1
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from sklearn.linear_model.sag import get_auto_step_size
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from sklearn.linear_model._sag import get_auto_step_size
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try:
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import lightning.classification as lightning_clf

‎benchmarks/bench_sparsify.py‎

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from scipy.sparse.csr import csr_matrix
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import numpy as np
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from sklearn.linear_model.stochastic_gradient import SGDRegressor
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from sklearn.linear_model import SGDRegressor
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from sklearn.metrics import r2_score
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np.random.seed(42)

‎doc/developers/develop.rst‎

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return self.classes_[np.argmax(D, axis=1)]
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In linear models, coefficients are stored in an array called ``coef_``, and the
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independent term is stored in ``intercept_``. ``sklearn.linear_model.base``
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independent term is stored in ``intercept_``. ``sklearn.linear_model._base``
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contains a few base classes and mixins that implement common linear model
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patterns.
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‎doc/modules/classes.rst‎

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manifold.locally_linear_embedding
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manifold.smacof
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manifold.spectral_embedding
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manifold.t_sne.trustworthiness
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manifold.trustworthiness
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.. _metrics_ref:
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svm.l1_min_c
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Low-level methods
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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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svm.libsvm.cross_validation
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svm.libsvm.decision_function
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svm.libsvm.fit
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svm.libsvm.predict
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svm.libsvm.predict_proba
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.. _tree_ref:
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:mod:`sklearn.tree`: Decision Trees

‎doc/modules/computing.rst‎

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, so latency should be equivalent.
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Here is an example using
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:class:`sklearn.linear_model.stochastic_gradient.SGDClassifier` with the
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:class:`sklearn.linear_model.SGDClassifier` with the
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``elasticnet`` penalty. The regularization strength is globally controlled by
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the ``alpha`` parameter. With a sufficiently high ``alpha``,
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one can then increase the ``l1_ratio`` parameter of ``elasticnet`` to

‎doc/modules/cross_validation.rst‎

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Or as a dict mapping scorer name to a predefined or custom scoring function::
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>>> from sklearn.metrics.scorer import make_scorer
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>>> from sklearn.metrics import make_scorer
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>>> scoring = {'prec_macro': 'precision_macro',
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... 'rec_macro': make_scorer(recall_score, average='macro')}
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>>> scores = cross_validate(clf, X, y, scoring=scoring,

‎doc/templates/index.html‎

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<li><strong>Gitter:</strong> <a href="https://gitter.im/scikit-learn/scikit-learn">gitter.im/scikit-learn</a></li>
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</ul>
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<form target="_top" id="paypal-form" method="post" action="https://www.paypal.com/cgi-bin/webscr">
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<input type="hidden" value="_s-xclick" name="cmd">
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<input type="hidden" value="74EYUMF3FTSW8" name="hosted_button_id">
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</form>
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<a class="btn btn-warning btn-big sk-donate-btn mb-1" onclick="document.getElementById('paypal-form').submit(); ">Help us, <strong>donate!</strong></a>
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<a class="btn btn-warning btn-big mb-1" href="about.html#citing-scikit-learn"><strong>Cite us!</strong></a>
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</div>
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<div class="col-md-4">

‎doc/themes/scikit-learn/static/nature.css_t‎

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#paypal-form {
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‎doc/whats_new/v0.21.rst‎

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- :func:`svm.SVC.decision_function` and
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:func:`multiclass.OneVsOneClassifier.decision_function`. |Fix|
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- :class:`linear_model.SGDClassifier` and any derived classifiers. |Fix|
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- Any model using the :func:`linear_model.sag.sag_solver` function with a `0`
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- Any model using the :func:`linear_model._sag.sag_solver` function with a `0`
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seed, including :class:`linear_model.LogisticRegression`,
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:class:`linear_model.LogisticRegressionCV`, :class:`linear_model.Ridge`,
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and :class:`linear_model.RidgeCV` with 'sag' solver. |Fix|

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