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  1. Part 4: Natural Language Processing with Fess

    $ pip install elasticsearch $ pip install numpy $ pip install...with the following command. $ pip install esanpy The usage method...
    fess.codelibs.org/articles/4/document.html
    Thu May 23 02:38:06 UTC 2024
      28.3K bytes
      10 views
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  2. Putting it all together — scikit-learn 1.5.0 do...

    1 ) pipe = Pipeline ( steps = [( "scaler"...), } search = GridSearchCV ( pipe , param_grid , n_jobs = 2 )...
    scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html
    Thu May 23 20:54:14 UTC 2024
      60.4K bytes
      1 views
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  3. sklearn.preprocessing.quantile_transform — scik...

    most risks of data leaking: pipe = make_pipeline(QuantileTransformer(),...
    scikit-learn.org/stable/modules/generated/sklearn.preprocessing.quantile_transform.html
    Sun May 19 20:00:39 UTC 2024
      26.5K bytes
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  4. getting_started.rst.txt

    create a pipeline object >>> pipe = make_pipeline( ... StandardScaler(),...# fit the whole pipeline >>> pipe.fit(X_train, y_train) Pipel...
    scikit-learn.org/stable/_sources/getting_started.rst.txt
    Sun May 19 20:00:39 UTC 2024
      10K bytes
     
  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
    Tue May 21 18:58:19 UTC 2024
      32.8K bytes
      2 views
     
  6. 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
    Thu May 23 20:54:15 UTC 2024
      53K bytes
     
  7. Recursive feature elimination — scikit-learn 1....

    ] ) pipe . fit ( X , y ) ranking = pipe . named_steps...), - 1 )) y = digits . target pipe = Pipeline ( [ ( "scaler" ,...
    scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_digits.html
    Thu May 23 20:54:14 UTC 2024
      91.1K bytes
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  8. 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 23 20:54:14 UTC 2024
      96.4K bytes
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  9. Getting Started — scikit-learn 1.5.0 documentation

    create a pipeline object >>> pipe = make_pipeline ( ... StandardScaler...# fit the whole pipeline >>> pipe . fit ( X_train , y_train )...
    scikit-learn.org/stable/getting_started.html
    Thu May 23 20:54:14 UTC 2024
      52.8K bytes
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      Similar Results (1)
     
  10. Logstash Reference [8.13] | Elastic

    logstash log4j lumberjack meetup pipe puppet_facter rabbitmq redis...nagios_nsca opentsdb pagerduty pipe rabbitmq redis redmine riak...
    www.elastic.co/guide/en/logstash/current/index.html
    Mon May 13 19:49:51 UTC 2024
      47.8K bytes
      1 views
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