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  1. Comparing Nearest Neighbors with and without Ne...

    test_size = 0.7 , random_state = 42 ) h = 0.05 # step size in...n_neighbors )) plt . text ( 0.9 , 0.1 , " {:.2f} " . format ( score...
    scikit-learn.org/stable/auto_examples/neighbors/plot_nca_classification.html
    Mon Mar 23 20:39:20 UTC 2026
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  2. Plot different SVM classifiers in the iris data...

    wspace = 0.4 , hspace = 0.4 ) X0 , X1 = X [:, 0 ], X [:, 1 ] for...plot the support vectors C = 1.0 # SVM regularization parameter...
    scikit-learn.org/stable/auto_examples/svm/plot_iris_svc.html
    Mon Mar 23 20:39:22 UTC 2026
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  3. sklearn.covariance — scikit-learn 1.8.0 documen...

    Methods and algorithms to robustly estimate covariance. They estimate the covariance of features at given sets of points, as well as the precision matrix defined as the inverse of the covariance. C...
    scikit-learn.org/stable/api/sklearn.covariance.html
    Mon Mar 23 20:39:21 UTC 2026
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  4. sklearn.ensemble — scikit-learn 1.8.0 documenta...

    Ensemble-based methods for classification, regression and anomaly detection. User guide. See the Ensembles: Gradient boosting, random forests, bagging, voting, stacking section for further details.
    scikit-learn.org/stable/api/sklearn.ensemble.html
    Mon Mar 23 20:39:21 UTC 2026
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  5. Nearest Centroid Classification — scikit-learn ...

    None 0.8133333333333334 0.2 0.82 # Authors: The...points plt . scatter ( X [:, 0 ], X [:, 1 ], c = y , cmap = cmap_bold...
    scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.html
    Mon Mar 23 20:39:21 UTC 2026
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  6. delayed — scikit-learn 1.8.0 documentation

    Changed in version 1.3: delayed was moved from sklearn.utils.fixes...sklearn.utils.parallel in scikit-learn 1.3. Parameters : function callable...
    scikit-learn.org/stable/modules/generated/sklearn.utils.parallel.delayed.html
    Mon Mar 23 20:39:21 UTC 2026
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  7. sklearn.multioutput — scikit-learn 1.8.0 docume...

    Multioutput regression and classification. The estimators provided in this module are meta-estimators: they require a base estimator to be provided in their constructor. The meta-estimator extends ...
    scikit-learn.org/stable/api/sklearn.multioutput.html
    Mon Mar 23 20:39:23 UTC 2026
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  8. 8. Dataset loading utilities — scikit-learn 1.8...

    1. Toy datasets 8.1.1. Iris plants dataset 8.1.2. Diabetes...digits dataset 8.1.4. Linnerrud dataset 8.1.5. Wine recognition dataset...
    scikit-learn.org/stable/datasets.html
    Mon Mar 23 20:39:23 UTC 2026
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  9. 9. Computing with scikit-learn — scikit-learn 1...

    1.1. Scaling with instances using out-of-core...Computing with scikit-learn # 9.1. Strategies to scale computationally:...
    scikit-learn.org/stable/computing.html
    Mon Mar 23 20:39:21 UTC 2026
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  10. 13. Choosing the right estimator — scikit-learn...

    xml version="1.0" encoding="UTF-8"?> START START...tough luck tough... <100K samples <100K... YES YES SGD Classifier...
    scikit-learn.org/stable/machine_learning_map.html
    Mon Mar 23 20:39:20 UTC 2026
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