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shuffle — scikit-learn 1.7.2 documentation
[2., 1.], [1., 0.]]) >>> y array([2, 1, 0]) >>>...= np . array ([[ 1. , 0. ], [ 2. , 1. ], [ 0. , 0. ]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html -
kmeans_plusplus — scikit-learn 1.7.2 docu...
2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2 ], [ 10 , 4...array([[10, 2], [ 1, 0]]) >>> indices array([3, 2]) Gallery...scikit-learn.org/stable/modules/generated/sklearn.cluster.kmeans_plusplus.html -
hamming_loss — scikit-learn 1.7.2 documen...
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 -
johnson_lindenstrauss_min_dim — scikit-le...
v||^2 < ||p(u) - p(v)||^2 < (1 + eps) ||u - v||^2 Where...>= 4 log(n_samples) / (eps^2 / 2 - eps^3 / 3) Note that the number...scikit-learn.org/stable/modules/generated/sklearn.random_projection.johnson_lindenstrauss_min_dim... -
KNeighborsRegressor — scikit-learn 1.7.2 ...
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html -
mean_pinball_loss — scikit-learn 1.7.2 do...
2 , 3 ] >>> mean_pinball_loss...mean_pinball_loss ( y_true , [ 0 , 2 , 3 ], alpha = 0.1 ) 0.03... >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_pinball_loss.html -
root_mean_squared_error — scikit-learn 1....
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>...>>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.root_mean_squared_error.html -
OPTICS — scikit-learn 1.7.2 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 -
kneighbors_graph — scikit-learn 1.7.2 doc...
p = 2 , metric_params = None , include_self...standard Euclidean distance when p = 2. See the documentation of scipy.spatial.distance...scikit-learn.org/stable/modules/generated/sklearn.neighbors.kneighbors_graph.html -
train_test_split — scikit-learn 1.7.2 doc...
2 1 4.9 3.0 1.4 0.2 2 4.7 3.2 1.3 0.2 3 4.6 3.1 1.5...73 6.1 2.8 4.7 1.2 18 5.7 3.8 1.7 0.3 118 7.7 2.6 6.9 2.3 78 6.0...scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html