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Results 21 - 30 of 131 for pipe (0.23 sec)

  1. World News: Latest International Headlines, Vid...

    ’ skeletal remains found in pipe of Wisconsin music store in...
    www.nbcnews.com/world
    Fri May 17 00:50:56 UTC 2024
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  2. Technology and Media News | NBC News

    ’ skeletal remains found in pipe of Wisconsin music store in...
    www.nbcnews.com/tech-media
    Fri May 17 00:51:25 UTC 2024
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  3. Sports News: Latest stories, videos, photos and...

    ’ skeletal remains found in pipe of Wisconsin music store in...
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    Fri May 17 00:51:01 UTC 2024
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  4. 6.3. Preprocessing data — scikit-learn 1.4.2 do...

    random_state = 42 ) >>> pipe = make_pipeline ( StandardScaler...(), LogisticRegression ()) >>> pipe . fit ( X_train , y_train )...
    scikit-learn.org/stable/modules/preprocessing.html
    Thu May 16 17:15:46 UTC 2024
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  5. grid_search.rst.txt

    tion import SelectKBest >>> pipe = Pipeline([ ... ('select',...8]} >>> search = GridSearchCV(pipe, param_grid, cv=5).fit(X, y)...
    scikit-learn.org/stable/_sources/modules/grid_search.rst.txt
    Thu May 16 17:15:45 UTC 2024
      33K bytes
      2 views
     
  6. 3.2. Tuning the hyper-parameters of an estimato...

    tion import SelectKBest >>> pipe = Pipeline ([ ... ( 'select'...>>> search = GridSearchCV ( pipe , param_grid , cv = 5 ) . fit...
    scikit-learn.org/stable/modules/grid_search.html
    Thu May 16 17:15:46 UTC 2024
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  7. NBC News - Breaking News & Top Stories - Latest...

    ’ skeletal remains found in pipe of Wisconsin music store in...about a dozen abstaining Nathan Papes / USA Today Network Republican...
    www.nbcnews.com
    Fri May 17 00:48:35 UTC 2024
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  8. One-Class SVM versus One-Class SVM using Stocha...

    1e-4 ) pipe_sgd = make_pipeline ( transform , clf_sgd ) pipe_sgd...y_pred_train_sgd = pipe_sgd . predict ( X_train ) y_pred_test_sgd = pipe_sgd...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgdocsvm_vs_ocsvm.html
    Thu May 16 17:15:46 UTC 2024
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  9. Pipelining: chaining a PCA and a logistic regre...

    1 ) pipe = Pipeline ( steps = [( "scaler"...), } search = GridSearchCV ( pipe , param_grid , n_jobs = 2 )...
    scikit-learn.org/stable/auto_examples/compose/plot_digits_pipe.html
    Thu May 16 17:15:46 UTC 2024
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  10. preprocessing.rst.txt

    random_state=42) >>> pipe = make_pipeline(StandardScaler(),..., LogisticRegression()) >>> pipe.fit(X_train, y_train) # apply...
    scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt
    Wed May 15 13:59:40 UTC 2024
      52.7K bytes
     
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