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feature_selection.rst.txt
the best features based on univariate statistical tests. It can...we can use a F-test to retrieve the two best features for a dataset...scikit-learn.org/stable/_sources/modules/feature_selection.rst.txt -
linear_model.rst.txt
cost of :math:`O(n_{\text{samples}} n_{\text{features}}^2)`, assuming...that :math:`n_{\text{samples}} \geq n_{\text{features}}`. .....scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
getting_started.rst.txt
X_test, y_train, y_test = train_test_split(X, y, random_state=0)...>>> X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)...scikit-learn.org/stable/_sources/getting_started.rst.txt -
glossary.rst.txt
common tests This refers to the tests run on almost every...``(train_idx, test_idx)`` pairs. Each of {train,test}_idx is a 1d...scikit-learn.org/stable/_sources/glossary.rst.txt -
faq.rst.txt
:ref:`text_feature_extraction` for the built-in *text vectorizers*....^^^^^^^^^^ scikit-learn is regularly tested and maintained to work with...scikit-learn.org/stable/_sources/faq.rst.txt -
classes.rst.txt
_text_feature_extraction_ref: From text --------- .....feature_extraction.text.CountVectorizer feature_extraction.text.HashingVectorizer...scikit-learn.org/stable/_sources/modules/classes.rst.txt -
grid_search.rst.txt
have identified the best candidate. The best candidate is identified...`factor=2` candidates: the best candidate is the best out of these 2 candidates....scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
roadmap.rst.txt
Improve scikit-learn common tests suite to make sure that (at.../ ordinal / English language text?") should also not need to be...scikit-learn.org/stable/_sources/roadmap.rst.txt -
clustering.rst.txt
math:: \text{ARI} = \frac{\text{RI} - E[\text{RI}]}{\max(\text{RI})...math:: \text{AMI} = \frac{\text{MI} - E[\text{MI}]}{\text{mean}(H(U),...scikit-learn.org/stable/_sources/modules/clustering.rst.txt -
ensemble.rst.txt
to est >>> mean_squared_error(y_test, est.predict(X_test)) 3.84......train_test_split >>> X_train, X_test, y_train, y_test = train_test_split(X,...scikit-learn.org/stable/_sources/modules/ensemble.rst.txt