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model_evaluation.rst.txt
_precision_recall_f_measure_metrics: Precision, recall and F-measures...1_score>`_ (:math:`F_\beta` and :math:`F_1` measures) can be...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
feature_selection.rst.txt
we can use a F-test to retrieve the two best...sklearn.feature_selection import f_classif >>> X, y = load_iris(return_X_y=True)...scikit-learn.org/stable/_sources/modules/feature_selection.rst.txt -
about.rst.txt
F. and Varoquaux, G. and Gramfort,...scikit-learn.org/stable/_sources/about.rst.txt -
linear_model.rst.txt
:math:`\ell_2` | :math:`\frac{1}{2}\|W\|_F^2 = \frac{1}{2}\sum_{i=1}^m\sum_{j=1}^{K}...:math:`\frac{1 - \rho}{2}\|W\|_F^2 + \rho \|W\|_{1,1}` | +---------...scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
ensemble.rst.txt
F(x_i))}{\partial F(x_i)} \right]_{F=F_{m - 1}}. .....\frac{\partial l(y_i, F(x_i))}{\partial F(x_i)} \right]_{F=F_{m - 1}}` is...scikit-learn.org/stable/_sources/modules/ensemble.rst.txt -
decomposition.rst.txt
F. Bach, J. Ponce, G. Sapiro, 2009..._ R. Jenatton, G. Obozinski, F. Bach, 2009 .. _kernel_PCA: Kernel...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
preprocessing.rst.txt
formula :math:`G^{-1}(F(X))` where :math:`F` is the cumulative distribution...distribution function :math:`F` then :math:`F(X)` is uniformly distributed...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
feature_extraction.rst.txt
'mpy f', 'py fo', 'umpy ', 'y fox'],...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
contributing.rst.txt
control this ratio with the `-f` flag. To run the full benchmark...scikit-learn.org/dev/_sources/developers/contributing.rst.txt -
faq.rst.txt
layouts (`X` C-contiguous or F-contiguous, sparse csr or csc)....scikit-learn.org/stable/_sources/faq.rst.txt