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Compare the effect of different scalers on data...
width = 0.1 , 0.22 bottom , height = 0.1 , 0.7 bottom_h =...width , 0.1 ] rect_histy = [ left_h , bottom , 0.05 , height...scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html -
The Johnson-Lindenstrauss bound for embedding w...
rate: 1.01 (0.09) Projected 300 samples from 130107 to 10000 in 7.567s...eps_range = np . linspace ( 0.01 , 0.99 , 100 ) # range of number of...scikit-learn.org/stable/auto_examples/miscellaneous/plot_johnson_lindenstrauss_bound.html -
One-class SVM with non-linear kernel (RBF) — sc...
reshape ( - 1 , 1 ), yy . reshape ( - 1 , 1 )], axis = 1 ) DecisionBoundaryDisp...OneClassSVM ( nu = 0.1 , kernel = "rbf" , gamma = 0.1 ) clf . fit (...scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html -
SVM-Anova: SVM with univariate feature selectio...
percentiles = ( 1 , 3 , 6 , 10 , 15 , 20 , 30 , 40 , 60 , 80 , 100 ) for.... xticks ( np . linspace ( 0 , 100 , 11 , endpoint = True )) plt...scikit-learn.org/stable/auto_examples/svm/plot_svm_anova.html -
sklearn.neighbors — scikit-learn 1.8.0 document...
The k-nearest neighbors algorithms. User guide. See the Nearest Neighbors section for further details.scikit-learn.org/stable/api/sklearn.neighbors.html -
Semi Supervised Classification — scikit-learn 1...
Examples concerning the sklearn.semi_supervised module. Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset Effect of varying threshold for self-training Label Propagati...scikit-learn.org/stable/auto_examples/semi_supervised/index.html -
1.5. Stochastic Gradient Descent — scikit-learn...
>>> X = [[ 0. , 0. ], [ 1. , 1. ]] >>> y = [ 0 , 1 ] >>> clf =...predict_proba ([[ 1. , 1. ]]) array([[0.00, 0.99]]) The concrete...scikit-learn.org/stable/modules/sgd.html -
5.1. Partial Dependence and Individual Conditio...
random_state = 0 ) . fit ( X , y ) >>> features = [ 0 , 1 , ( 0 , 1 )] >>>...n_estimators = 100 , learning_rate = 1.0 , ... max_depth = 1 , random_state...scikit-learn.org/stable/modules/partial_dependence.html -
8.3. Generated datasets — scikit-learn 1.8.0 do...
make_circles ( noise = 0.1 , factor = 0.3 , random_state = 0 ) ax1 . scatter...noise = 0.1 , random_state = 0 ) ax2 . scatter ( X [:, 0 ], X [:,...scikit-learn.org/stable/datasets/sample_generators.html -
8.4. Loading other datasets — scikit-learn 1.8....
forget to scale to the range 0 - 1 as done in the following example....'ARFF', 'upload_date': '2017-11-08T16:00:15', 'licence': 'Public',...scikit-learn.org/stable/datasets/loading_other_datasets.html