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IncrementalPCA — scikit-learn 1.8.0 documentation
[ - 2 , - 1 ], [ - 3 , - 2 ], ... [ 1 , 1 ], [ 2 , 1 ], [...O(batch_size * n_features ** 2) , but only 2 * batch_size samples remain...scikit-learn.org/stable/modules/generated/sklearn.decomposition.IncrementalPCA.html -
incr_mean_variance_axis — scikit-learn 1....
2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2 , 5...>>> scale = np . array ([ 2 , 3 , 2 ]) >>> csr = sparse...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.incr_mean_variance_axis.html -
1.4. Support Vector Machines — scikit-learn 1.8...
[ 2 , 2 ]] >>> y = [ 0.5 , 2.5 ] >>> regr = svm...values: >>> clf . predict ([[ 2. , 2. ]]) array([1]) SVMs decision...scikit-learn.org/stable/modules/svm.html -
QuadraticDiscriminantAnalysis — scikit-learn 1....
2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2 , 2 ]) >>>...- 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
Two-class AdaBoost — scikit-learn 1.8.0 documen...
cov = 2.0 , n_samples = 200 , n_features = 2 , n_classes = 2 , random_state...= 300 , n_features = 2 , n_classes = 2 , random_state = 1 ) X...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html -
Polynomial and Spline interpolation — scikit-le...
x_0 ** 2 , x_0 ** 3 , ... , x_0 ** degree...degree ], [ 1 , x_1 , x_1 ** 2 , x_1 ** 3 , ... , x_1 ** degree...scikit-learn.org/stable/auto_examples/linear_model/plot_polynomial_interpolation.html -
ParameterGrid — scikit-learn 1.8.0 documentation
{ 'a' : 2 , 'b' : True }, { 'a' : 2 , 'b' : False }])...>>> param_grid = { 'a' : [ 1 , 2 ], 'b' : [ True , False ]} >>>...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterGrid.html -
MultiTaskLasso — scikit-learn 1.8.0 documentation
2 ], [ 2 , 4 ]], [[ 0 , 0 ], [ 1 , 1 ], [ 2 , 3 ]]) ...Lasso is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ 2 _Fro + alpha...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLasso.html -
homogeneity_completeness_v_measure — scikit-lea...
2 , 2 ], [ 0 , 0 , 1 , 2 , 2 , 2 ] >>> homogen...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_completeness_v_measure.html -
mean_pinball_loss — scikit-learn 1.8.0 document...
2 , 3 ] >>> mean_pinball_loss ( y_true , [ 0 , 2 , 3 ],...mean_pinball_loss ( y_true , [ 1 , 2 , 4 ], alpha = 0.1 ) 0.3... >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_pinball_loss.html