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Results 981 - 990 of over 10,000 for 2 (0.31 seconds)

  1. Sparse coding with a precomputed dictionary &#8...

    ) ** 2 / width ** 2 ) * np . exp ( - (( x - center ) ** 2 ) /.../ ( 2 * width ** 2 )) ) return x def ricker_matrix ( width , resolution...
    scikit-learn.org/stable/auto_examples/decomposition/plot_sparse_coding.html
    Thu Nov 27 16:33:55 GMT 2025
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  2. Gaussian Mixture Model Selection — scikit...

    convert to degrees v = 2.0 * np . sqrt ( 2.0 ) * np . sqrt ( v )...random . randn ( n_samples , 2 ), C ) # general component_2 =...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_selection.html
    Thu Nov 27 16:33:57 GMT 2025
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  3. Support Vector Machines — scikit-learn 1....

    Examples concerning the sklearn.svm module. One-class SVM with non-linear kernel (RBF) Plot classification boundaries with different SVM Kernels Plot different SVM classifiers in the iris dataset P...
    scikit-learn.org/stable/auto_examples/svm/index.html
    Thu Nov 27 16:33:57 GMT 2025
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  4. Missing Value Imputation — scikit-learn 1...

    Examples concerning the sklearn.impute module. Imputing missing values before building an estimator Imputing missing values with variants of IterativeImputer
    scikit-learn.org/stable/auto_examples/impute/index.html
    Thu Nov 27 16:33:54 GMT 2025
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  5. Kernel Density Estimation — scikit-learn ...

    This example shows how kernel density estimation (KDE), a powerful non-parametric density estimation technique, can be used to learn a generative model for a dataset. With this generative model in ...
    scikit-learn.org/stable/auto_examples/neighbors/plot_digits_kde_sampling.html
    Thu Nov 27 16:33:57 GMT 2025
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  6. Demonstration of k-means assumptions — sc...

    subplots ( nrows = 2 , ncols = 2 , figsize = ( 12 , 12 ))...plt . subplots ( nrows = 2 , ncols = 2 , figsize = ( 12 , 12 ))...
    scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html
    Thu Nov 27 16:33:57 GMT 2025
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  7. Map data to a normal distribution — sciki...

    figaspect ( 2 )) axes = axes . flatten () axes_idxs..., 9 ), ( 1 , 4 , 7 , 10 ), ( 2 , 5 , 8 , 11 ), ( 12 , 15 , 18...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_map_data_to_normal.html
    Thu Nov 27 16:33:55 GMT 2025
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  8. Scaling the regularization parameter for SVCs &...

    logspace ( - 2.3 , - 1.3 , 10 ) train_sizes =...param_range = Cs , cv = cv , n_jobs = 2 , ) results [ label ] = test_scores...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_scale_c.html
    Thu Nov 27 16:33:57 GMT 2025
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  9. 8.13.2 release notes | Enterprise Search docume...

    2 release notes IMPORTANT : This...the latest documentation . 8.13.2 release notes No changes since...
    www.elastic.co/guide/en/enterprise-search/8.19/release-notes-8.13.2.html
    Mon Oct 20 16:31:47 GMT 2025
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  10. Feature importances with a forest of trees &#82...

    n_classes = 2 , random_state = 0 , shuffle =...None min_samples_split  2 min_samples_leaf  1 min_...
    scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html
    Thu Nov 27 16:33:55 GMT 2025
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