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  1. Compare the effect of different scalers on data...

    Feature 0 (median income in a block) and feature 5 (average house occupancy) of the California Housing dataset have very different scales and contain some very large outliers. These two characteris...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html
    Sat Aug 23 16:32:03 UTC 2025
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  2. Class Likelihood Ratios to measure classificati...

    This example demonstrates the class_likelihood_ratios function, which computes the positive and negative likelihood ratios ( LR+, LR-) to assess the predictive power of a binary classifier. As we w...
    scikit-learn.org/stable/auto_examples/model_selection/plot_likelihood_ratios.html
    Sat Aug 23 16:32:03 UTC 2025
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  3. Linear and Quadratic Discriminant Analysis with...

    This example plots the covariance ellipsoids of each class and the decision boundary learned by LinearDiscriminantAnalysis(LDA) and QuadraticDiscriminantAnalysis(QDA). The ellipsoids display the do...
    scikit-learn.org/stable/auto_examples/classification/plot_lda_qda.html
    Sat Aug 23 16:32:04 UTC 2025
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  4. Robust linear model estimation using RANSAC — s...

    In this example, we see how to robustly fit a linear model to faulty data using the RANSAC algorithm. The ordinary linear regressor is sensitive to outliers, and the fitted line can easily be skewe...
    scikit-learn.org/stable/auto_examples/linear_model/plot_ransac.html
    Sat Aug 23 16:32:03 UTC 2025
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  5. Label Propagation digits: Demonstrating perform...

    This example demonstrates the power of semisupervised learning by training a Label Spreading model to classify handwritten digits with sets of very few labels. The handwritten digit dataset has 179...
    scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits.html
    Sat Aug 23 16:32:03 UTC 2025
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  6. Overview of multiclass training meta-estimators...

    In this example, we discuss the problem of classification when the target variable is composed of more than two classes. This is called multiclass classification. In scikit-learn, all estimators su...
    scikit-learn.org/stable/auto_examples/multiclass/plot_multiclass_overview.html
    Sat Aug 23 16:32:03 UTC 2025
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  7. Label Propagation digits: Active learning — sci...

    Demonstrates an active learning technique to learn handwritten digits using label propagation. We start by training a label propagation model with only 10 labeled points, then we select the top fiv...
    scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni...
    Sat Aug 23 16:32:03 UTC 2025
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  8. HuberRegressor vs Ridge on dataset with strong ...

    Fit Ridge and HuberRegressor on a dataset with outliers. The example shows that the predictions in ridge are strongly influenced by the outliers present in the dataset. The Huber regressor is less ...
    scikit-learn.org/stable/auto_examples/linear_model/plot_huber_vs_ridge.html
    Sat Aug 23 16:32:03 UTC 2025
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  9. 7.9. Transforming the prediction target (y) — s...

    Transforming the prediction target ( y): These are transformers that are not intended to be used on features, only on supervised learning targets. See also Transforming target in regression if you ...
    scikit-learn.org/stable/modules/preprocessing_targets.html
    Sat Aug 23 16:32:03 UTC 2025
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  10. Compressive sensing: tomography reconstruction ...

    This example shows the reconstruction of an image from a set of parallel projections, acquired along different angles. Such a dataset is acquired in computed tomography(CT). Without any prior infor...
    scikit-learn.org/stable/auto_examples/applications/plot_tomography_l1_reconstruction.html
    Sat Aug 23 16:32:03 UTC 2025
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