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  1. sklearn.experimental — scikit-learn 1.8.0...

    Importable modules that enable the use of experimental features or estimators.
    scikit-learn.org/stable/api/sklearn.experimental.html
    Mon Jan 19 11:28:23 GMT 2026
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  2. 5.1. Partial Dependence and Individual Conditio...

    Partial dependence plots (PDP) and individual conditional expectation (ICE) plots can be used to visualize and analyze interaction between the target response 1 and a set of input features of inter...
    scikit-learn.org/stable/modules/partial_dependence.html
    Mon Jan 19 11:28:24 GMT 2026
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  3. Manifold learning on handwritten digits: Locall...

    We illustrate various embedding techniques on the digits dataset. Load digits dataset: We will load the digits dataset and only use six first of the ten available classes. We can plot the first hun...
    scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html
    Mon Jan 19 11:28:24 GMT 2026
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  4. Plot the decision surface of decision trees tra...

    Plot the decision surface of a decision tree trained on pairs of features of the iris dataset. See decision tree for more information on the estimator. For each pair of iris features, the decision ...
    scikit-learn.org/stable/auto_examples/tree/plot_iris_dtc.html
    Mon Jan 19 11:28:23 GMT 2026
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  5. Plot classification probability — scikit-...

    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
    Mon Jan 19 11:28:25 GMT 2026
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  6. Nearest Neighbors Classification — scikit...

    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
    Mon Jan 19 11:28:24 GMT 2026
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  7. Underfitting vs. Overfitting — scikit-lea...

    This example demonstrates the problems of underfitting and overfitting and how we can use linear regression with polynomial features to approximate nonlinear functions. The plot shows the function ...
    scikit-learn.org/stable/auto_examples/model_selection/plot_underfitting_overfitting.html
    Mon Jan 19 11:28:25 GMT 2026
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  8. Gaussian Mixture Models — scikit-learn 1....

    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
    Mon Jan 19 11:28:25 GMT 2026
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  9. Nearest Neighbors regression — scikit-lea...

    Demonstrate the resolution of a regression problem using a k-Nearest Neighbor and the interpolation of the target using both barycenter and constant weights. Generate sample data: Here we generate ...
    scikit-learn.org/stable/auto_examples/neighbors/plot_regression.html
    Mon Jan 19 11:28:25 GMT 2026
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  10. RBF SVM parameters — scikit-learn 1.8.0 d...

    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
    Mon Jan 19 11:28:25 GMT 2026
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