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make_scorer — scikit-learn 1.5.2 documentation
version 1.4: needs_proba is deprecated in version 1.4 and will...version 1.4: needs_threshold is deprecated in version 1.4 and will...scikit-learn.org/stable/modules/generated/sklearn.metrics.make_scorer.html -
affinity_propagation — scikit-learn 1.5.2 docum...
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2...>>> labels array([0, 0, 0, 1, 1, 1]) Gallery examples # Visualizing...scikit-learn.org/stable/modules/generated/sklearn.cluster.affinity_propagation.html -
3.5. Validation curves: plotting scores to eval...
array([[1. , 0.93..., 1. , 1. , 0.96...], [1. , 0.96..., 1. , 1....0.96..., 0.93...], [1.... , 0.93..., 1.... , 1.... , 0.9... ]])...scikit-learn.org/stable/modules/learning_curve.html -
MethodMapping — scikit-learn 1.5.2 documentation
Added in version 1.3. add ( * , caller , callee )...scikit-learn.org/stable/modules/generated/sklearn.utils.metadata_routing.MethodMapping.html -
Ledoit-Wolf vs OAS estimation — scikit-learn 1....
covariance matrix (AR(1) process) r = 0.1 real_cov = toeplitz (...plot MSE plt . subplot ( 2 , 1 , 1 ) plt . errorbar ( n_samples_range...scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html -
TargetEncoder — scikit-learn 1.5.2 documentation
1 ] * 15 + [ 20.4 ] * 5 + [ 20.1 ] * 25 + [ 21.2...scikit-learn 1.3 Release Highlights for scikit-learn 1.3 Comparing...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.TargetEncoder.html -
Effect of varying threshold for self-training —...
mean ( axis = 1 ), yerr = scores . std ( axis = 1 ), capsize =...( axis = 1 ), yerr = amount_labeled . std ( axis = 1 ), capsize...scikit-learn.org/stable/auto_examples/semi_supervised/plot_self_training_varying_threshold.html -
A demo of the mean-shift clustering algorithm —...
centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1 , - 1 ]] X , _ = make_blobs...matplotlib.pyplot as plt plt . figure ( 1 ) plt . clf () colors = [ "#dede00"...scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html -
PCA example with Iris Data-set — scikit-learn 1...
1 ] . mean () + 1.5 , X [ y == label , 2...features 1 and 2 Sparsity Example: Fitting only features 1 and 2...scikit-learn.org/stable/auto_examples/decomposition/plot_pca_iris.html -
make_blobs — scikit-learn 1.5.2 documentation
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...2) >>> y array([0, 0, 1, 0, 2, 2, 2, 1, 1, 0]) >>> X , y = make_blobs...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_blobs.html