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  1. 7. Dataset transformations — scikit-learn...

    scikit-learn provides a library of transformers, which may clean (see Preprocessing data), reduce (see Unsupervised dimensionality reduction), expand (see Kernel Approximation) or generate (see Fea...
    scikit-learn.org/stable/data_transforms.html
    Mon Jan 19 11:28:25 GMT 2026
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  2. Probability Calibration curves — scikit-l...

    When performing classification one often wants to predict not only the class label, but also the associated probability. This probability gives some kind of confidence on the prediction. This examp...
    scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html
    Mon Jan 19 11:28:25 GMT 2026
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  3. Compare BIRCH and MiniBatchKMeans — sciki...

    This example compares the timing of BIRCH (with and without the global clustering step) and MiniBatchKMeans on a synthetic dataset having 25,000 samples and 2 features generated using make_blobs. B...
    scikit-learn.org/stable/auto_examples/cluster/plot_birch_vs_minibatchkmeans.html
    Mon Jan 19 11:28:24 GMT 2026
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  4. Model Complexity Influence — scikit-learn...

    Demonstrate how model complexity influences both prediction accuracy and computational performance. We will be using two datasets:,- Diabetes dataset for regression. This dataset consists of 10 mea...
    scikit-learn.org/stable/auto_examples/applications/plot_model_complexity_influence.html
    Mon Jan 19 11:28:23 GMT 2026
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  5. Wikipedia principal eigenvector — scikit-...

    A classical way to assert the relative importance of vertices in a graph is to compute the principal eigenvector of the adjacency matrix so as to assign to each vertex the values of the components ...
    scikit-learn.org/stable/auto_examples/applications/wikipedia_principal_eigenvector.html
    Mon Jan 19 11:28:23 GMT 2026
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  6. Semi Supervised Classification — scikit-l...

    Examples concerning the sklearn.semi_supervised module. Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset Effect of varying threshold for self-training Label Propagati...
    scikit-learn.org/stable/auto_examples/semi_supervised/index.html
    Mon Jan 19 11:28:25 GMT 2026
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  7. Glossary of Common Terms and API Elements &#821...

    other relevant parts of the documentation which do so. By linking...overviewed in the contributor documentation . The specific interfaces...
    scikit-learn.org/stable/glossary.html
    Mon Jan 19 11:28:23 GMT 2026
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  8. Gradient Boosting Out-of-Bag estimates — ...

    Out-of-bag (OOB) estimates can be a useful heuristic to estimate the “optimal” number of boosting iterations. OOB estimates are almost identical to cross-validation estimates but they can be comput...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html
    Mon Jan 19 11:28:24 GMT 2026
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  9. 1.4. Support Vector Machines — scikit-lea...

    Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection. The advantages of support vector machines are: Effective in high ...
    scikit-learn.org/stable/modules/svm.html
    Mon Jan 19 11:28:25 GMT 2026
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  10. Online learning of a dictionary of parts of fac...

    This example uses a large dataset of faces to learn a set of 20 x 20 images patches that constitute faces. From the programming standpoint, it is interesting because it shows how to use the online ...
    scikit-learn.org/stable/auto_examples/cluster/plot_dict_face_patches.html
    Mon Jan 19 11:28:25 GMT 2026
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