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make_sparse_coded_signal — scikit-learn 1.7.2 d...
Gallery examples: Orthogonal Matching Pursuitscikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_coded_signal.html -
pairwise_distances_argmin_min — scikit-learn 1....
Skip to main content Back to top Ctrl + K GitHub Choose version pairwise_distances_argmin_min # sklearn.metrics. pair...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances_argmin_min.html -
Forecasting of CO2 level on Mona Loa dataset us...
co2_kernel 50**2 * RBF(length_scale=50) + 2**2 * RBF(length_scale=100)...GaussianProcessRegre(kernel=50**2 * RBF(length_scale=50) + 2**2 * RBF(length_scale=100)...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_co2.html -
Manifold learning on handwritten digits: Locall...
zorder = 2 , ) shown_images = np . array...(( X [ i ] - shown_images ) ** 2 , 1 ) if np . min ( dist ) < 4e-3...scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html -
sklearn.naive_bayes — scikit-learn 1.7.2 docume...
Naive Bayes algorithms. These are supervised learning methods based on applying Bayes’ theorem with strong (naive) feature independence assumptions. User guide. See the Naive Bayes section for furt...scikit-learn.org/stable/api/sklearn.naive_bayes.html -
estimator_checks_generator — scikit-learn 1.7.2...
Skip to main content Back to top Ctrl + K GitHub Choose version estimator_checks_generator # sklearn.utils.estimator_...scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.estimator_checks_generat... -
sklearn.random_projection — scikit-learn 1.7.2 ...
Random projection transformers. Random projections are a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional ...scikit-learn.org/stable/api/sklearn.random_projection.html -
Examples based on real world datasets — scikit-...
Applications to real world problems with some medium sized datasets or interactive user interface. Compressive sensing: tomography reconstruction with L1 prior (Lasso) Faces recognition example usi...scikit-learn.org/stable/auto_examples/applications/index.html -
sklearn.kernel_approximation — scikit-learn 1.7...
Approximate kernel feature maps based on Fourier transforms and count sketches. User guide. See the Kernel Approximation section for further details.scikit-learn.org/stable/api/sklearn.kernel_approximation.html -
fetch_species_distributions — scikit-learn 1.7....
Gallery examples: Species distribution modeling Kernel Density Estimate of Species Distributionsscikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_species_distributions.html