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Factor Analysis (with rotation) to visualize pa...
2 , 3 ]) ax . set_xticklabels (...) ax . set_yticks ([ 0 , 1 , 2 , 3 ]) ax . set_yticklabels (...scikit-learn.org/stable/auto_examples/decomposition/plot_varimax_fa.html -
OneToOneFeatureMixin — scikit-learn 1.8.0...
2 ], [ 3 , 4 ]]) >>> MyEstimator...scikit-learn.org/stable/modules/generated/sklearn.base.OneToOneFeatureMixin.html -
Installation sur Linux (Procédure détaillée)
2/fess-15.3.2.tar.gz $ tar -xzf fess-15.3.2.tar.gz $...s-15.3.2/fess-15.3.2.rpm $ sudo rpm -ivh fess-15.3.2.rpm Configuration...fess.codelibs.org/fr/15.3/install/install-linux.html -
DictVectorizer — scikit-learn 1.8.0 docum...
'bar' : 2 }, { 'foo' : 3 , 'baz'...( D ) >>> X array([[2., 0., 1.], [0., 1., 3.]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html -
recall_score — scikit-learn 1.8.0 documen...
2 , 0 , 1 , 2 ] >>> y_pred = [ 0 , 2 , 1 , 0...scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html -
Varying regularization in Multi-layer Perceptro...
n_features = 2 , n_redundant = 0 , n_informative = 2 , random_state.... random . RandomState ( 2 ) X += 2 * rng . uniform ( size =...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_alpha.html -
OrthogonalMatchingPursuitCV — scikit-lear...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...coefficient of determination, \(R^2\) , is defined as \((1 - \frac{u}{v})\)...scikit-learn.org/stable/modules/generated/sklearn.linear_model.OrthogonalMatchingPursuitCV.html -
Gaussian Mixture Model Selection — scikit...
convert to degrees v = 2.0 * np . sqrt ( 2.0 ) * np . sqrt ( v )...random . randn ( n_samples , 2 ), C ) # general component_2 =...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_selection.html -
Log Configuration
/^\d{4}-\d{2}-\d{2}/ format1 /^(?<time>\d{4}-\d{2}-\d{2} \d{...\d{2}:\d{2}:\d{2},\d{3}) \[(?<thread>.*?)\] (?<level&g...fess.codelibs.org/15.3/config/admin-logging.html -
LassoCV — scikit-learn 1.8.0 documentation
it is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ 2 _Fro + alpha...X = np . array ([[ 1 , 2 , 3.1 ], [ 2.3 , 5.4 , 4.3 ]]) . T >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoCV.html