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Varying regularization in Multi-layer Perceptro...
() - 0.5 , X [:, 0 ] . max () + 0.5 y_min , y_max = X [:, 1 ]...] . min () - 0.5 , X [:, 1 ] . max () + 0.5 xx , yy = np . meshgrid...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_alpha.html -
Compare Stochastic learning strategies for MLPC...
"sgd" , "learning_rate" : "constant" , "momentum" : 0.9 , "nesterovs_momentum"..."sgd" , "learning_rate" : "constant" , "momentum" : 0.9 , "nesterovs_momentum"...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_training_curves.html -
Concatenating multiple feature extraction metho...
ts=1, features__univ_select__k=1, svm__C=0.1 [CV 1/5; 1/18] END...nts=1, features__univ_select__k=1, svm__C=0.1;, score=0.933 total...scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html -
Effect of transforming the targets in regressio...
y_pred ) . items (): ax . plot ([], [], " " , label = f " { name }...= 100 , random_state = 0 ) y = np . expm1 (( y + abs ( y . min...scikit-learn.org/stable/auto_examples/compose/plot_transformed_target.html -
Map data to a normal distribution — scikit-lear...
colors = [ "#D81B60" , "#0188FF" , "#FFC107" , "#B7A2FF" , "#000000"...flatten () axes_idxs = [ ( 0 , 3 , 6 , 9 ), ( 1 , 4 , 7 , 10 ), ( 2...scikit-learn.org/stable/auto_examples/preprocessing/plot_map_data_to_normal.html -
Decision boundary of semi-supervised classifier...
1 , 1 ), 0 : ( 0 , 0 , 0.9 ), 1 : ( 1 , 0 , 0 ), 2 : ( 0.8 , 0.6...x_min , x_max = X [:, 0 ] . min () - 1 , X [:, 0 ] . max () + 1...scikit-learn.org/stable/auto_examples/semi_supervised/plot_semi_supervised_versus_svm_iris.html -
SVM with custom kernel — scikit-learn 1.7.2 doc...
kernel: (2 0) k(X, Y) = X ( ) Y.T (0 1) """ M = np . array ([[ 2...2 , 0 ], [ 0 , 1.0 ]]) return np . dot ( np . dot ( X , M ), Y...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
Scaling the regularization parameter for SVCs —...
= np . logspace ( - 2.3 , - 1.3 , 10 ) train_sizes = np . linspace...linestyle = "--" , color = "grey" , alpha = 0.7 ) # plot results...scikit-learn.org/stable/auto_examples/svm/plot_svm_scale_c.html -
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