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Underfitting vs. Overfitting — scikit-learn 1.6...
0 ) n_samples = 30 degrees = [ 1 , 4 , 15 ] X = np . sort ( np...ax , xticks = (), yticks = ()) polynomial_features = PolynomialFeatures...scikit-learn.org/stable/auto_examples/model_selection/plot_underfitting_overfitting.html -
Demo of affinity propagation clustering algorit...
): class_members = labels == k cluster_center = X [ cluster_centers_indices...labels_true = make_blobs ( n_samples = 300 , centers = centers ,...scikit-learn.org/stable/auto_examples/cluster/plot_affinity_propagation.html -
AdditiveChi2Sampler — scikit-learn 1.6.1 docume...
y = load_digits ( return_X_y = True ) >>> chi2sampler = AdditiveChi2Sampler...>>> clf = SGDClassifier ( max_iter = 5 , random_state = 0 , tol...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.AdditiveChi2Sampler.html -
plot_multi_metric_evaluation.ipynb
\n alpha=0.1 if sample == \"test\" else 0,\n color=color,\n )\n... style,\n color=color,\n alpha=1 if sample == \"test\" else 0.7,\n...scikit-learn.org/stable/_downloads/f57e1ee55d4c7a51949d5c26b3af07bb/plot_multi_metric_evaluation.... -
SVC — scikit-learn 1.6.1 documentation
C = 1.0 , kernel = 'rbf' , degree = 3 , gamma = 'scale'...coef0 = 0.0 , shrinking = True , probability = False , tol = 0.001...scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html -
HistGradientBoostingRegressor — scikit-learn 1....
n_iter_no_change = 10 , tol = 1e-07 , verbose = 0 , random_state = None )...learning_rate = 0.1 , max_iter = 100 , max_leaf_nodes = 31 , max_depth...scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html -
L1-based models for Sparse Signals — scikit-lea...
linthresh = 10e-4 , vmin =- 1 , vmax = 1 ), cbar_kws = { "label"...import r2_score t0 = time () lasso = Lasso ( alpha = 0.14 ) . fit (...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
Monotonic Constraints — scikit-learn 1.6.1 docu...
X = np . c_ [ f_0 , f_1 ] noise = rng . normal ( loc = 0.0 ,...y , "o" , alpha = 0.3 , zorder =- 1 , color = "tab:green" ) disp...scikit-learn.org/stable/auto_examples/ensemble/plot_monotonic_constraints.html -
SVM: Weighted samples — scikit-learn 1.6.1 docu...
c = y , s = 100 * sample_weight , alpha = 0.9 , cmap = plt...( xx , yy , Z , alpha = 0.75 , cmap = plt . cm . bone ) axis...scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html -
fetch_openml — scikit-learn 1.6.1 documentation
n_retries : int = 3 , delay : float = 1.0 , parser : str = 'auto' ,...: str | None = None , * , version : str | int = 'active' , data_id...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_openml.html