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  1. Combine predictors using stacking — scikit-lear...

    (): df = fetch_openml ( name = "house_prices" , as_frame = True...True ) X = df . data y = df . target features = [ "YrSold" , "HeatingQC"...
    scikit-learn.org/stable/auto_examples/ensemble/plot_stack_predictors.html
    Thu Jul 03 11:42:05 UTC 2025
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  2. 7.1. Pipelines and composite estimators — sciki...

    >>> iris = load_iris () >>> pipe = Pipeline ( steps = [ ... (...memory = cachedir ) >>> pipe Pipeline(memory=..., steps=[('reduce_dim',...
    scikit-learn.org/stable/modules/compose.html
    Thu Jul 03 11:42:06 UTC 2025
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  3. 4. Metadata Routing — scikit-learn 1.7.0 docume...

    sample_weight = True ) >>> sel = SelectKBest ( k = 2 ) >>> pipe = make_pipeline...sample_weight = True ) >>> lr = LogisticRegressionCV ( ... cv = GroupKFold...
    scikit-learn.org/stable/metadata_routing.html
    Thu Jul 03 11:42:06 UTC 2025
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  4. Faces recognition example using eigenfaces and ...

    subplots_adjust ( bottom = 0 , left = 0.01 , right = 0.99 , top = 0.90 , hspace...random_state = 42 ) scaler = StandardScaler () X_train = scaler ....
    scikit-learn.org/stable/auto_examples/applications/plot_face_recognition.html
    Thu Jul 03 11:42:05 UTC 2025
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  5. 11. Common pitfalls and recommended practices —...

    random_state = 42 >>> X , y = make_regression ( random_state = random_state...random_state = 42 ) >>> gbc = HistGradientBoosting ( random_state = 1 )...
    scikit-learn.org/stable/common_pitfalls.html
    Thu Jul 03 11:42:05 UTC 2025
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  6. Spectral clustering for image segmentation — sc...

    as np l = 100 x , y = np . indices (( l , l )) center1 = ( 28 ,...center2 = ( 40 , 50 ) center3 = ( 67 , 58 ) center4 = ( 24 , 70...
    scikit-learn.org/stable/auto_examples/cluster/plot_segmentation_toy.html
    Thu Jul 03 11:42:05 UTC 2025
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  7. Displaying Pipelines — scikit-learn 1.7.0 docum...

    default is display='diagram' . set_config ( display = "diagram" ) pipe...change to display='text' . set_config ( display = "text" ) pipe...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_pipeline_display.html
    Thu Jul 03 11:42:05 UTC 2025
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  8. Successive Halving Iterations — scikit-learn 1....

    n_samples = 400 , n_features = 12 , random_state = rng ) clf = RandomForestClassifi...( legend = False , alpha = 0.6 ) labels = [ f "iter= { i } \n...
    scikit-learn.org/stable/auto_examples/model_selection/plot_successive_halving_iterations.html
    Thu Jul 03 11:42:06 UTC 2025
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  9. KNeighborsClassifier — scikit-learn 1.7.0 docum...

    leaf_size = 30 , p = 2 , metric = 'minkowski' , metric_params = None...n_neighbors = 5 , * , weights = 'uniform' , algorithm = 'auto' ,...
    scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html
    Thu Jul 03 11:42:05 UTC 2025
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  10. KNeighborsRegressor — scikit-learn 1.7.0 docume...

    leaf_size = 30 , p = 2 , metric = 'minkowski' , metric_params = None...n_neighbors = 5 , * , weights = 'uniform' , algorithm = 'auto' ,...
    scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html
    Thu Jul 03 11:42:05 UTC 2025
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