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3.1. Cross-validation: evaluating estimator per...
kernel = 'linear' , C = 1 , random_state = 0 ) >>> scores = cross_validate...(60,)) >>> clf = svm . SVC ( kernel = 'linear' , C = 1 ) . fit (...scikit-learn.org/stable/modules/cross_validation.html -
fetch_lfw_people — scikit-learn 1.7.0 documenta...
download_if_missing = True , return_X_y = False , n_retries = 3 , delay = 1.0..., data_home = None , funneled = True , resize = 0.5 , min_faces_per_person...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_lfw_people.html -
Column Transformer with Mixed Types — scikit-le...
y = fetch_openml ( "titanic" , version = 1 , as_frame = True...attribute: # X = titanic.frame.drop('survived', axis=1) # y = titanic.frame['survived']...scikit-learn.org/stable/auto_examples/compose/plot_column_transformer_mixed_types.html -
Lasso model selection via information criteria ...
y = load_diabetes ( return_X_y = True , as_frame = True )...aic_criterion , color = "tab:blue" , marker = "o" , label = "AIC criterion"...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_lars_ic.html -
RBFSampler — scikit-learn 1.7.0 documentation
gamma = 1.0 , n_components = 100 , random_state = None ) [source]...rbf_feature = RBFSampler ( gamma = 1 , random_state = 1 ) >>> X_features...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.RBFSampler.html -
Release Highlights for scikit-learn 1.7 — sciki...
ng = True ) X , y = make_classification ( random_state = 0 )...set_fit_request ( X_val = True , y_val = True ) model = Pipeline ([( "sc"...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_7_0.html -
Release Highlights for scikit-learn 1.0 — sciki...
n_iter_no_change = 10 , tol = 1e-7 , verbose = 0 , random_state = None ,...loss = "squared_error" , learning_rate = 0.1 , max_iter = 100...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html -
TweedieRegressor — scikit-learn 1.7.0 documenta...
power = 0.0 , alpha = 1.0 , fit_intercept = True , link = 'auto'...'auto' , solver = 'lbfgs' , max_iter = 100 , tol = 0.0001 , warm_start...scikit-learn.org/stable/modules/generated/sklearn.linear_model.TweedieRegressor.html -
SVM with custom kernel — scikit-learn 1.7.0 doc...
cmap = plt . cm . Paired , ax = ax , response_method = "predict"...1 ], c = Y , cmap = plt . cm . Paired , edgecolors = "k" ) plt...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
Gaussian process classification (GPC) on iris d...
y = np . array ( iris . target , dtype = int ) h = 0.02 #...play with iris = datasets . load_iris () X = iris . data [:,...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_iris.html