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Kernel PCA — scikit-learn 1.7.0 documentation
y = make_circles ( n_samples = 1_000 , factor = 0.3 , noise...test_ax ) = plt . subplots ( ncols = 2 , sharex = True , sharey...scikit-learn.org/stable/auto_examples/decomposition/plot_kernel_pca.html -
plot_release_highlights_1_7_0.py
""" ========== Release Highlights for scikit-learn 1.7 ==========...========== .. currentmodule:: sklearn We are pleased to announce the...scikit-learn.org/stable/_downloads/27dd4dbb41dee53fc86e0d5b6d3254d3/plot_release_highlights_1_7_0.py -
decomposition.rst.txt
_decompositions: ========== Decomposing signals in components...(matrix factorization problems) ========== .. currentmodule:: sklearn.decomposition...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
OOB Errors for Random Forests — scikit-learn 1....
y = make_classification ( n_samples = 500 , n_features = 25...n_clusters_per_class = 1 , n_informative = 15 , random_state = RANDOM_STATE...scikit-learn.org/stable/auto_examples/ensemble/plot_ensemble_oob.html -
LogisticRegressionCV — scikit-learn 1.7.0 docum...
Cs = 10 , fit_intercept = True , cv = None , dual = False...penalty = 'l2' , scoring = None , solver = 'lbfgs' , tol = 0.0001...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html -
plot_release_highlights_1_7_0.rst.txt
y: ========== Release Highlights for scikit-learn 1.7 ==========...========== .. currentmodule:: sklearn We are pleased to announce the...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_7_0.r... -
OPTICS — scikit-learn 1.7.0 documentation
min_samples = 5 , max_eps = inf , metric = 'minkowski' , p = 2 , metric_params...metric_params = None , cluster_method = 'xi' , eps = None , xi = 0.05...scikit-learn.org/stable/modules/generated/sklearn.cluster.OPTICS.html -
Plot the support vectors in LinearSVC — scikit-...
clf = LinearSVC ( C = C , loss = "hinge" , random_state = 42 )...1 ], c = y , s = 30 , cmap = plt . cm . Paired ) ax = plt . gca...scikit-learn.org/stable/auto_examples/svm/plot_linearsvc_support_vectors.html -
MDS — scikit-learn 1.7.0 documentation
n_components = 2 , * , metric = True , n_init = 'warn' , max_iter = 300...verbose = 0 , eps = 1e-06 , n_jobs = None , random_state = None...scikit-learn.org/stable/modules/generated/sklearn.manifold.MDS.html -
CalibratedClassifierCV — scikit-learn 1.7.0 doc...
estimator = None , * , method = 'sigmoid' , cv = None , n_jobs = None..., y = make_classification ( n_samples = 100 , n_features = 2 ,...scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibratedClassifierCV.html