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  1. Test with permutations the significance of a cl...

    This example demonstrates the use of permutation_test_score to evaluate the significance of a cross-validated score using permutations. Dataset: We will use the Iris plants dataset, which consists ...
    scikit-learn.org/stable/auto_examples/model_selection/plot_permutation_tests_for_classification.html
    Mon Dec 22 11:58:31 GMT 2025
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  2. Image denoising using kernel PCA — scikit...

    This example shows how to use KernelPCA to denoise images. In short, we take advantage of the approximation function learned during fit to reconstruct the original image. We will compare the result...
    scikit-learn.org/stable/auto_examples/applications/plot_digits_denoising.html
    Mon Dec 22 11:58:30 GMT 2025
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  3. Blind source separation using FastICA — s...

    An example of estimating sources from noisy data. Independent component analysis (ICA) is used to estimate sources given noisy measurements. Imagine 3 instruments playing simultaneously and 3 micro...
    scikit-learn.org/stable/auto_examples/decomposition/plot_ica_blind_source_separation.html
    Mon Dec 22 11:58:29 GMT 2025
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  4. Swiss Roll And Swiss-Hole Reduction — sci...

    This notebook seeks to compare two popular non-linear dimensionality techniques, T-distributed Stochastic Neighbor Embedding (t-SNE) and Locally Linear Embedding (LLE), on the classic Swiss Roll da...
    scikit-learn.org/stable/auto_examples/manifold/plot_swissroll.html
    Mon Dec 22 11:58:29 GMT 2025
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  5. Permutation Importance with Multicollinear or C...

    In this example, we compute the permutation_importance of the features to a trained RandomForestClassifier using the Breast cancer Wisconsin (diagnostic) dataset. The model can easily get about 97%...
    scikit-learn.org/stable/auto_examples/inspection/plot_permutation_importance_multicollinear.html
    Mon Dec 22 11:58:30 GMT 2025
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  6. Early stopping of Stochastic Gradient Descent &...

    Stochastic Gradient Descent is an optimization technique which minimizes a loss function in a stochastic fashion, performing a gradient descent step sample by sample. In particular, it is a very ef...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_early_stopping.html
    Mon Dec 22 11:58:30 GMT 2025
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  7. Poisson regression and non-normal loss — ...

    This example illustrates the use of log-linear Poisson regression on the French Motor Third-Party Liability Claims dataset from 1 and compares it with a linear model fitted with the usual least squ...
    scikit-learn.org/stable/auto_examples/linear_model/plot_poisson_regression_non_normal_loss.html
    Mon Dec 22 11:58:29 GMT 2025
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  8. Outlier detection on a real data set — sc...

    This example illustrates the need for robust covariance estimation on a real data set. It is useful both for outlier detection and for a better understanding of the data structure. We selected two ...
    scikit-learn.org/stable/auto_examples/applications/plot_outlier_detection_wine.html
    Mon Dec 22 11:58:30 GMT 2025
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  9. Compare Stochastic learning strategies for MLPC...

    This example visualizes some training loss curves for different stochastic learning strategies, including SGD and Adam. Because of time-constraints, we use several small datasets, for which L-BFGS ...
    scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_training_curves.html
    Mon Dec 22 11:58:29 GMT 2025
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  10. Varying regularization in Multi-layer Perceptro...

    A comparison of different values for regularization parameter ‘alpha’ on synthetic datasets. The plot shows that different alphas yield different decision functions. Alpha is a parameter for regula...
    scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_alpha.html
    Mon Dec 22 11:58:29 GMT 2025
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