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  1. Comparing Random Forests and Histogram Gradient...

    fig = make_subplots ( rows = 1 , cols = 2 , shared_yaxes = True...), legend = dict ( x = 0.72 , y = 0.05 , traceorder = "normal"...
    scikit-learn.org/stable/auto_examples/ensemble/plot_forest_hist_grad_boosting_comparison.html
    Sat Nov 23 04:49:16 UTC 2024
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  2. sigmoid_kernel — scikit-learn 1.5.2 documentation

    Y = None , gamma = None , coef0 = 1 ) [source] #...array. If None , uses Y=X . gamma float, default=None Coefficient of...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.sigmoid_kernel.html
    Sat Nov 23 04:49:15 UTC 2024
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  3. ndcg_score — scikit-learn 1.5.2 documentation

    k = None , sample_weight = None , ignore_ties = False ).../ 2 = .75 >>> ndcg_score ( true_relevance , scores , k = 1 )...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.ndcg_score.html
    Sat Nov 23 04:49:15 UTC 2024
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  4. Approximate nearest neighbors in TSNE — scikit-...

    n_samples = 20_000 )), ] n_iter = 500 perplexity = 30 metric = "euclidean"...n_neighbors = 5 , metric = "euclidean" , method = "sw-graph" ,...
    scikit-learn.org/stable/auto_examples/neighbors/approximate_nearest_neighbors.html
    Sat Nov 23 04:49:14 UTC 2024
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  5. KDTree — scikit-learn 1.5.2 documentation

    return_distance == False (d,i) if return_distance == True d ndarray...count if count_only == True ind if count_only == False and return_distance...
    scikit-learn.org/stable/modules/generated/sklearn.neighbors.KDTree.html
    Sat Nov 23 04:49:15 UTC 2024
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  6. preprocessing.rst.txt

    _preprocessing: ========== Preprocessing data ========== .. currentmodule::...removal and variance scaling ========== **Standardization** of datasets...
    scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt
    Fri Nov 22 23:53:26 UTC 2024
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  7. Time-related feature engineering — scikit-learn...

    figsize = ( 12 , 4 )) y . hist ( bins = 30 , ax = ax ) _ = ax ....axes = plt . subplots ( nrows = 2 , ncols = 3 , figsize = ( 13...
    scikit-learn.org/stable/auto_examples/applications/plot_cyclical_feature_engineering.html
    Sat Nov 23 04:49:15 UTC 2024
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  8. Comparison of Manifold Learning methods — sciki...

    axs = plt . subplots ( nrows = 2 , ncols = 2 , figsize = ( 7...y , z = points . T fig , ax = plt . subplots ( figsize = ( 6 ,...
    scikit-learn.org/stable/auto_examples/manifold/plot_compare_methods.html
    Sat Nov 23 04:49:16 UTC 2024
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  9. MultiOutputClassifier — scikit-learn 1.5.2 docu...

    y = make_multilabel_classification ( n_classes = 3 , random_state...random_state = 0 ) >>> clf = MultiOutputClassifie ( LogisticRegression...
    scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputClassifier.html
    Sat Nov 23 04:49:14 UTC 2024
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  10. 6.6. Random Projection — scikit-learn 1.5.2 doc...

    johnson_lindenstrauss_min_dim ( n_samples = 1e6 , eps = 0.5 ) 663 >>> johnson_l...johnson_lindenstrauss_min_dim ( n_samples = 1e6 , eps = [ 0.5 , 0.1 , 0.01 ]) array([...
    scikit-learn.org/stable/modules/random_projection.html
    Fri Nov 22 23:53:27 UTC 2024
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