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  1. Ensemble methods — scikit-learn 1.6.1 documenta...

    Examples concerning the sklearn.ensemble module. Categorical Feature Support in Gradient Boosting Combine predictors using stacking Comparing Random Forests and Histogram Gradient Boosting models C...
    scikit-learn.org/stable/auto_examples/ensemble/index.html
    Mon Apr 21 17:07:38 UTC 2025
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  2. Feature Selection — scikit-learn 1.6.1 document...

    Examples concerning the sklearn.feature_selection module. Comparison of F-test and mutual information Model-based and sequential feature selection Pipeline ANOVA SVM Recursive feature elimination R...
    scikit-learn.org/stable/auto_examples/feature_selection/index.html
    Mon Apr 21 17:07:38 UTC 2025
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  3. Decision Trees — scikit-learn 1.6.1 documentation

    Examples concerning the sklearn.tree module. Decision Tree Regression Plot the decision surface of decision trees trained on the iris dataset Post pruning decision trees with cost complexity prunin...
    scikit-learn.org/stable/auto_examples/tree/index.html
    Mon Apr 21 17:07:38 UTC 2025
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  4. Dataset examples — scikit-learn 1.6.1 documenta...

    Examples concerning the sklearn.datasets module. Plot randomly generated multilabel dataset
    scikit-learn.org/stable/auto_examples/datasets/index.html
    Mon Apr 21 17:07:39 UTC 2025
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  5. Multioutput methods — scikit-learn 1.6.1 docume...

    Examples concerning the sklearn.multioutput module. Multilabel classification using a classifier chain
    scikit-learn.org/stable/auto_examples/multioutput/index.html
    Mon Apr 21 17:07:39 UTC 2025
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  6. Confusion matrix — scikit-learn 1.6.1 documenta...

    Example of confusion matrix usage to evaluate the quality of the output of a classifier on the iris data set. The diagonal elements represent the number of points for which the predicted label is e...
    scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html
    Mon Apr 21 17:07:39 UTC 2025
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  7. Multiclass methods — scikit-learn 1.6.1 documen...

    Examples concerning the sklearn.multiclass module. Overview of multiclass training meta-estimators
    scikit-learn.org/stable/auto_examples/multiclass/index.html
    Mon Apr 21 17:07:38 UTC 2025
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  8. Release Highlights for scikit-learn 1.3 — sciki...

    We are pleased to announce the release of scikit-learn 1.3! Many bug fixes and improvements were added, as well as some new key features. We detail below a few of the major features of this release...
    scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_3_0.html
    Mon Apr 21 17:07:38 UTC 2025
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  9. 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 Apr 21 17:07:38 UTC 2025
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  10. SVM-Anova: SVM with univariate feature selectio...

    This example shows how to perform univariate feature selection before running a SVC (support vector classifier) to improve the classification scores. We use the iris dataset (4 features) and add 36...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_anova.html
    Mon Apr 21 17:07:39 UTC 2025
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