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Decision Tree Regression with AdaBoost — ...
linewidth = 2 ) plt . plot ( X , y_2 , color = colors [ 2 ], label..."n_estimators=300" , linewidth = 2 ) plt . xlabel ( "data"...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_regression.html -
Version 0.15 — scikit-learn 1.8.0 documen...
Marsi 2 csytracy 2 LK 2 Vlad Niculae 2 Laurent Direr 2 Erik Shilts...Liau 2 abhishek thakur 2 James Yu 2 Rohit Sivaprasad 2 Roland...scikit-learn.org/stable/whats_new/v0.15.html -
make_friedman1 — scikit-learn 1.8.0 docum...
2 ] - 0.5 ) ** 2 + 10 * X [:, 3 ] + 5 *...in Friedman [1] and Breiman [2]. Inputs X are independent features...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html -
plot_classifier_comparison.py
make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...scikit-learn.org/stable/_downloads/2da0534ab0e0c8241033bcc2d912e419/plot_classifier_comparison.py -
KNeighborsTransformer — scikit-learn 1.8....
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which..., metric = 'minkowski' , p = 2 , metric_params = None , n_jobs...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsTransformer.html -
Ordinary Least Squares and Ridge Regression ...
[ 2 ]] # Use only one feature X_train...ax = plt . subplots ( ncols = 2 , figsize = ( 10 , 5 ), sharex...scikit-learn.org/stable/auto_examples/linear_model/plot_ols_ridge.html -
all_estimators — scikit-learn 1.8.0 docum...
'tuple'> >>> estimators [: 2 ] [('ARDRegression', <class...) >>> classifiers [: 2 ] [('AdaBoostClassifier',...scikit-learn.org/stable/modules/generated/sklearn.utils.discovery.all_estimators.html -
GMM covariances — scikit-learn 1.8.0 docu...
covariances_ [ n ][: 2 , : 2 ] elif gmm . covariance_type...covariances = gmm . covariances_ [: 2 , : 2 ] elif gmm . covariance_type...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_covariances.html -
Attack Discovery | Elastic
Elastic Observability in action: 2-minute quick demo Watch this short,...Explore Search Elasticsearch in 2 minutes In this demo, we show...www.elastic.co/demo-gallery/security-attack-discovery -
Normal, Ledoit-Wolf and OAS Linear Discriminant...
centers = [[ - 2 ], [ 2 ]]) # add non-discriminative...features_samples_ratio , acc_clf1 , linewidth = 2 , label = "LDA" , color...scikit-learn.org/stable/auto_examples/classification/plot_lda.html