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Gaussian Mixture Models — scikit-learn 1.7.2 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 -
sklearn.calibration — scikit-learn 1.7.2 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_20newsgroups — scikit-learn 1.7.2 documen...
Gallery examples: Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation Biclustering documents with the Spectral Co-clustering algorithm Column Transformer with He...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_20newsgroups.html -
sklearn.cluster — scikit-learn 1.7.2 documentation
Popular unsupervised clustering algorithms. User guide. See the Clustering and Biclustering sections for further details.scikit-learn.org/stable/api/sklearn.cluster.html -
shrunk_covariance — scikit-learn 1.7.2 document...
Skip to main content Back to top Ctrl + K GitHub Choose version shrunk_covariance # sklearn.covariance. shrunk_covari...scikit-learn.org/stable/modules/generated/sklearn.covariance.shrunk_covariance.html -
sklearn.decomposition — scikit-learn 1.7.2 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 -
top_k_accuracy_score — scikit-learn 1.7.2 docum...
2 , 2 ]) >>> y_score = np . array ([[ 0.5 , 0.2 , 0.2 ], #...top 2 ... [ 0.3 , 0.4 , 0.2 ], # 1 is in top 2 ... [ 0.2 , 0.4...scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html -
Plot the decision surfaces of ensembles of tree...
2 , w_pad = 0.2 , pad = 2.5 ) plt . show ()...pair in ([ 0 , 1 ], [ 0 , 2 ], [ 2 , 3 ]): for model in models...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_iris.html -
SGD: Maximum margin separating hyperplane — sci...
centers = 2 , random_state = 0 , cluster_std...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.html -
Various Agglomerative Clustering on a 2D embedd...
SpectralEmbedding ( n_components = 2 ) . fit_transform ( X ) print...scikit-learn.org/stable/auto_examples/cluster/plot_digits_linkage.html