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OPTICS — scikit-learn 1.7.1 documentation
2 (1999): 49-60. [ 2 ] Schubert, Erich, Michael...>>> X = np . array ([[ 1 , 2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8...scikit-learn.org/stable/modules/generated/sklearn.cluster.OPTICS.html -
KBinsDiscretizer — scikit-learn 1.7.1 documenta...
[ 2., 2., 2., 1.], [ 2., 2., 2., 2.]]) Sometimes...>>> X = [[ - 2 , 1 , - 4 , - 1 ], ... [ - 1 , 2 , - 3 , - 0.5...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KBinsDiscretizer.html -
LocallyLinearEmbedding — scikit-learn 1.7.1 doc...
(n_components + 1) / 2 . see reference [2] modified : use the...n_neighbors = 5 , n_components = 2 , reg = 0.001 , eigen_solver =...scikit-learn.org/stable/modules/generated/sklearn.manifold.LocallyLinearEmbedding.html -
NearestNeighbors — scikit-learn 1.7.1 documenta...
2 , return_distance = False ) array([[2, 0]]...) >>>...array([[2]])) As you can see, it returns [[0.5]], and [[2]], which...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestNeighbors.html -
decomposition.rst.txt
\frac{1}{2} ||X - Y||_{\mathrm{Fro}}^2 = \frac{1}{2} \sum_{i,j}...Y) = \frac{1}{2} ||X - Y||_{Fro}^2 = \frac{1}{2} \sum_{i,j} (X_{ij}...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
r2_score — scikit-learn 1.7.1 documentation
y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 ] >>> r2_score...y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 + 1e-8...scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
ElasticNet — scikit-learn 1.7.1 documentation
function: 1 / ( 2 * n_samples ) * || y - Xw ||^ 2_2 + alpha * l1_ratio...it is: 1 / ( 2 * n_samples ) * || y - Xw ||^ 2_2 + alpha * l1_ratio...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html -
MiniBatchNMF — scikit-learn 1.7.1 documentation
||H||_{Fro}^2,\end{aligned}\end{align} \] where \(||A||_{Fro}^2 = \sum_{i,j}...array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchNMF.html -
BayesianRidge — scikit-learn 1.7.1 documentation
[ 2 , 2 ]], [ 0 , 1 , 2 ]) BayesianRidge() >>>...1e-06 , alpha_2 = 1e-06 , lambda_1 = 1e-06 , lambda_2 = 1e-06 , alpha_init...scikit-learn.org/stable/modules/generated/sklearn.linear_model.BayesianRidge.html -
hamming_loss — scikit-learn 1.7.1 documentation
2 , 3 , 4 ] >>> y_true = [ 2 , 2 , 3 , 4 ] >>>...[ 1 , 1 ]]), np . zeros (( 2 , 2 ))) 0.75 Gallery examples #...scikit-learn.org/stable/modules/generated/sklearn.metrics.hamming_loss.html