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Plot classification probability — scikit-learn ...
This example illustrates the use of sklearn.inspection.DecisionBoundaryDisplay to plot the predicted class probabilities of various classifiers in a 2D feature space, mostly for didactic purposes. ...scikit-learn.org/stable/auto_examples/classification/plot_classification_probability.html -
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 -
RBF SVM parameters — scikit-learn 1.7.2 documen...
This example illustrates the effect of the parameters gamma and C of the Radial Basis Function (RBF) kernel SVM. Intuitively, the gamma parameter defines how far the influence of a single training ...scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html -
Nearest Neighbors Classification — scikit-learn...
This example shows how to use KNeighborsClassifier. We train such a classifier on the iris dataset and observe the difference of the decision boundary obtained with regards to the parameter weights...scikit-learn.org/stable/auto_examples/neighbors/plot_classification.html -
estimate_bandwidth — scikit-learn 1.7.2 documen...
Gallery examples: Comparing different clustering algorithms on toy datasets A demo of the mean-shift clustering algorithmscikit-learn.org/stable/modules/generated/sklearn.cluster.estimate_bandwidth.html -
f_classif — scikit-learn 1.7.2 documentation
Gallery examples: Univariate Feature Selection Pipeline ANOVA SVM SVM-Anova: SVM with univariate feature selectionscikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html -
confusion_matrix — scikit-learn 1.7.2 documenta...
Gallery examples: Visualizations with Display Objects Post-tuning the decision threshold for cost-sensitive learning Release Highlights for scikit-learn 1.5 Label Propagation digits: Active learningscikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
f1_score — scikit-learn 1.7.2 documentation
Gallery examples: Probability Calibration curves Precision-Recall Semi-supervised Classification on a Text Datasetscikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.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 -
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