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sklearn.calibration — scikit-learn 1.5.2 docume...
Methods for calibrating predicted probabilities. User guide. See the Probability calibration section for further details. Visualization:scikit-learn.org/stable/api/sklearn.calibration.html -
fetch_openml — scikit-learn 1.5.2 documentation
Gallery examples: Release Highlights for scikit-learn 1.4 Release Highlights for scikit-learn 1.2 Release Highlights for scikit-learn 1.1 Release Highlights for scikit-learn 0.22 Categorical Featur...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_openml.html -
Gaussian Mixture Models — scikit-learn 1.5.2 do...
Examples concerning the sklearn.mixture module. Concentration Prior Type Analysis of Variation Bayesian Gaussian Mixture Density Estimation for a Gaussian mixture GMM Initialization Methods GMM cov...scikit-learn.org/stable/auto_examples/mixture/index.html -
shrunk_covariance — scikit-learn 1.5.2 document...
Skip to main content Back to top Ctrl + K GitHub shrunk_covariance # sklearn.covariance. shrunk_covariance ( emp_cov ...scikit-learn.org/stable/modules/generated/sklearn.covariance.shrunk_covariance.html -
estimate_bandwidth — scikit-learn 1.5.2 documen...
Gallery examples: A demo of the mean-shift clustering algorithm Comparing different clustering algorithms on toy datasetsscikit-learn.org/stable/modules/generated/sklearn.cluster.estimate_bandwidth.html -
sparse_encode — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub sparse_encode # sklearn.decomposition. sparse_encode ( X , dictionar...scikit-learn.org/stable/modules/generated/sklearn.decomposition.sparse_encode.html -
sklearn.decomposition — scikit-learn 1.5.2 docu...
Matrix decomposition algorithms. These include PCA, NMF, ICA, and more. Most of the algorithms of this module can be regarded as dimensionality reduction techniques. User guide. See the Decomposing...scikit-learn.org/stable/api/sklearn.decomposition.html -
lars_path — scikit-learn 1.5.2 documentation
Gallery examples: Lasso path using LARSscikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path.html -
f_classif — scikit-learn 1.5.2 documentation
Gallery examples: Pipeline ANOVA SVM Univariate Feature Selection SVM-Anova: SVM with univariate feature selectionscikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html -
minmax_scale — scikit-learn 1.5.2 documentation
Gallery examples: Restricted Boltzmann Machine features for digit classification Compare the effect of different scalers on data with outliersscikit-learn.org/stable/modules/generated/sklearn.preprocessing.minmax_scale.html