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Introducing the set_output API — scikit-l...
798301 -1.271411 -1.327605 12 -1.244466 -0.086944 -1.327407 -1.459074...60 5.0 2.0 3.5 1.0 1 4.9 3.0 1.4 0.2 8 4.4 2.9 1.4 0.2 93 5.0 2.3...scikit-learn.org/stable/auto_examples/miscellaneous/plot_set_output.html -
Visualizations with Display Objects — sci...
deprecated:: 1.8 `penalty` was deprecated in version 1.8 and will...with `0 = l1_ratio = 1`. Setting `l1_ratio=1` gives a pure L1-penalty,...scikit-learn.org/stable/auto_examples/miscellaneous/plot_display_object_visualization.html -
make_biclusters — scikit-learn 1.8.0 docu...
shape[1]) The indicators for cluster membership...for biclustering. References [ 1 ] Dhillon, I. S. (2001, August)....scikit-learn.org/stable/modules/generated/sklearn.datasets.make_biclusters.html -
2.3. Clustering — scikit-learn 1.8.0 docu...
1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2...0 , 1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2...scikit-learn.org/stable/modules/clustering.html -
Successive Halving Iterations — scikit-le...
[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...scikit-learn.org/stable/auto_examples/model_selection/plot_successive_halving_iterations.html -
make_checkerboard — scikit-learn 1.8.0 do...
shape[1]) The indicators for cluster membership...for biclustering. References [ 1 ] Kluger, Y., Basri, R., Chang,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_checkerboard.html -
FrozenEstimator — scikit-learn 1.8.0 docu...
scikit-learn 1.6 Release Highlights for scikit-learn 1.6 On this...scikit-learn.org/stable/modules/generated/sklearn.frozen.FrozenEstimator.html -
Plot classification probability — scikit-...
GaussianProcessClass ( kernel = 1.0 * RBF ([ 1.0 , 1.0 ])), "Logistic...LogisticRegression ( C = 0.1 ), "Logistic regression \n (C=1)" : LogisticRegression...scikit-learn.org/stable/auto_examples/classification/plot_classification_probability.html -
SVM: Weighted samples — scikit-learn 1.8....
n_clusters_per_class = 1 , class_sep = 1.1 , weights = [ 0.9 , 0.1 ], random_state...( X_plot [:, 0 ], X_plot [:, 1 ], c = y_plot , s = 100 * sample_weight...scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html -
RBF SVM parameters — scikit-learn 1.8.0 d...
1 , 1e2 ] gamma_2d_range = [ 1e-1 , 1 , 1e1 ] classifiers...np.float64(1.0), 'gamma': np.float64(0.1)} with a score...scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html