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  1. 1.10. Decision Trees — scikit-learn 1.5.2 docum...

    >>> X = [[ 0 , 0 ], [ 1 , 1 ]] >>> Y = [ 0 , 1 ] >>> clf = tree...filled = True , rounded = True , ... special_characters = True...
    scikit-learn.org/stable/modules/tree.html
    Thu Nov 21 22:17:08 UTC 2024
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  2. Harris Rakes In New Cash, Trump Threatens 'Nine...

    fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...
    digg.com/politics/link/harris-fundraising-abortion-texas-liz-cheney-trump
    Mon Nov 04 01:18:05 UTC 2024
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  3. Donald Trump Won Gen Z Men Fair And Square, Her...

    fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...fill="none" viewBox="0 0 24 24" stroke-width="1.5" stroke="currentColor">...
    digg.com/politics/link/donald-trump-gen-z-men-2024-election
    Thu Nov 14 01:21:30 UTC 2024
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  4. Concatenating multiple feature extraction metho...

    ents=1, features__univ_select__k=1, svm__C=0.1;, score=0.933...ents=1, features__univ_select__k=1, svm__C=0.1;, score=0.933...
    scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html
    Thu Nov 21 22:17:09 UTC 2024
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  5. Unlock the Power of Your Data with RAG using Ve...

    init(project=PROJECT, location=LOCATION) model = GenerativeM...image = Part.from_data( mime_type="image/jpeg", data=image_data)...
    www.elastic.co/search-labs/blog/unlock-power-of-data-with-rag-vertex-ai-elasticsearch
    Mon Nov 11 00:57:21 UTC 2024
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  6. RidgeCV — scikit-learn 1.5.2 documentation

    scoring = None , cv = None , gcv_mode = None , store_cv_results...store_cv_results = None , alpha_per_target = False , store_cv_values = 'deprecated'...
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeCV.html
    Thu Nov 21 22:17:10 UTC 2024
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  7. bootstrap.js

    g=B(h),_="y"===f?n:r,b="y"===f?s:o,v=i.rects.refe...H(t,e,i){void 0===e&&(e=!1),void 0===i&&(i=!1);var n=t.getBoundi...
    scikit-learn.org/dev/_static/scripts/bootstrap.js
    Wed Nov 20 19:47:15 UTC 2024
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  8. Pixel importances with a parallel forest of tre...

    mask = y < 5 X = X [ mask ] y = y [ mask ] A random...forest = RandomForestClassifi ( n_estimators = 750 , n_jobs = n_jobs...
    scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances_faces.html
    Thu Nov 21 22:17:09 UTC 2024
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  9. Probabilistic predictions with Gaussian process...

    train_size = 50 rng = np . random . RandomState ( 0 ) X = rng . uniform...train_size ], c = "k" , label = "Train data" , edgecolors = ( 0 , 0 ,...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc.html
    Thu Nov 21 22:17:09 UTC 2024
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  10. Nearest Centroid Classification — scikit-learn ...

    c = y , cmap = cmap_bold , edgecolor = "k" , s = 20 ) plt...shrinkage , np . mean ( y == y_pred )) _ , ax = plt . subplots () DecisionBoundaryDisp...
    scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.html
    Thu Nov 21 22:17:10 UTC 2024
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