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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 -
3.2. Tuning the hyper-parameters of an estimato...
6 * 2 = 12 35 // 2 = 17 12 * 2 = 24 17 // 2 = 8 24 * 2 = 48 8...3 (=min_resources) 70 (=n_candidates) 3 * 2 = 6 70 // 2 = 35...scikit-learn.org/stable/modules/grid_search.html -
Probability calibration of classifiers — scikit...
): this_X = X_train [ y_train == this_y ] this_sw = sw_train [...n_samples = n_samples , centers = centers , shuffle = False , random_state...scikit-learn.org/stable/auto_examples/calibration/plot_calibration.html -
Comparing random forests and the multi-output m...
edgecolor = "k" , c = "navy" , s = s , marker = "s" , alpha = a , label...edgecolor = "k" , c = "c" , s = s , marker = "^" , alpha = a , label...scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html -
BaggingRegressor — scikit-learn 1.6.1 documenta...
n_informative = 2 , n_targets = 1 , ... random_state = 0 , shuffle = False...estimator = None , n_estimators = 10 , * , max_samples = 1.0 , max_features...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html -
DetCurveDisplay — scikit-learn 1.6.1 documentation
sample_weight = None , pos_label = None , name = None , ax = None ,..., test_size = 0.4 , random_state = 0 ) >>> clf = SVC ( random_state...scikit-learn.org/stable/modules/generated/sklearn.metrics.DetCurveDisplay.html -
kneighbors_graph — scikit-learn 1.6.1 documenta...
mode = 'connectivity' , metric = 'minkowski' , p = 2 , metric_params...metric_params = None , include_self = False , n_jobs = None ) [source]...scikit-learn.org/stable/modules/generated/sklearn.neighbors.kneighbors_graph.html -
Forecasting of CO2 level on Mona Loa dataset us...
fetch_openml co2 = fetch_openml ( data_id = 41187 , as_frame = True ) co2...length_scale = 1.0 , periodicity = 1.0 , periodicity_bounds = "fixed"...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_co2.html -
GraphicalLasso — scikit-learn 1.6.1 documentation
alpha = 0.01 , * , mode = 'cd' , covariance = None , tol = 0.0001...enet_tol = 0.0001 , max_iter = 100 , verbose = False , eps = np.f...scikit-learn.org/stable/modules/generated/sklearn.covariance.GraphicalLasso.html -
Demonstration of k-means assumptions — scikit-l...
( X [ y == 0 ][: 500 ], X [ y == 1 ][: 100 ], X [ y == 2 ][: 10...axs = plt . subplots ( nrows = 2 , ncols = 2 , figsize = ( 12...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html