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KFold — scikit-learn 1.8.0 documentation
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...1 , 2 , 3 , 4 ]) >>> kf = KFold ( n_splits = 2 ) >>>...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html -
L1-based models for Sparse Signals — scik...
linspace ( - 2 , 2 , n_samples ) freqs = 2 * np . pi * np ....time_step + 2 * ( rng . random_sample () - 0.5 )) X [:, i ] += 0.2 * rng...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
haversine_distances — scikit-learn 1.8.0 ...
data must be 2. \[D(x, y) = 2\arcsin[\sqrt{\sin^2((x_{lat} - y_{lat})...y_{lat}) / 2) + \cos(x_{lat})\cos(y_{lat})\ sin^2((x_{lon} -...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.haversine_distances.html -
Robust vs Empirical covariance estimate —...
subplot ( 2 , 1 , 1 ) lw = 2 plt . errorbar ( range_n_outliers...font_prop ) plt . subplot ( 2 , 1 , 2 ) x_size = range_n_outliers...scikit-learn.org/stable/auto_examples/covariance/plot_robust_vs_empirical_covariance.html -
Label Propagation digits: Active learning ̵...
0 24 0] [ 0 0 0 0 2 1 0 2 2 27]] Iteration 2 __________ Label...0 0 0 0 0 25 0] [ 0 0 0 0 2 1 0 2 2 27]] Iteration 1 __________...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni... -
ShuffleSplit — scikit-learn 1.8.0 documen...
2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Test: index=[5 2] Fold 1: Train: index=[4 0 2 5] Test: index=[1...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
make_gaussian_quantiles — scikit-learn 1....
int64(2), np.int64(0), np.int64(1), np.int64(0), np.int64(2)] Gallery...n_samples = 100 , n_features = 2 , n_classes = 3 , shuffle = True...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_gaussian_quantiles.html -
unique_labels — scikit-learn 1.8.0 docume...
2 , 3 , 4 ], [ 2 , 2 , 3 , 4 ]) array([1, 2, 3, 4]) >>>...unique_labels ([ 1 , 2 , 10 ], [ 5 , 11 ]) array([ 1, 2, 5, 10, 11])...scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.unique_labels.html -
Plot randomly generated multilabel dataset R...
1500 * p_c ** 2 , color = COLORS . take ([ 1 , 2 , 4 ]), ) ax...means the class is present: 1 2 3 Color Y N N Red N Y N Blue N...scikit-learn.org/stable/auto_examples/datasets/plot_random_multilabel_dataset.html -
7.3. Preprocessing data — scikit-learn 1....
2. , 1. , 0.1], [4.4, 2.2, 1.1, 0.1], [4.4, 2.2, 1.2, 0.1],...4.1, 6.7, 2.5], [7.7, 4.2, 6.7, 2.5], [7.9, 4.4, 6.9, 2.5]]) Thus...scikit-learn.org/stable/modules/preprocessing.html