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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 -
Selecting dimensionality reduction with Pipelin...
load_digits ( return_X_y = True ) pipe = Pipeline ( [ ( "scaling" ,...f)" ] grid = GridSearchCV ( pipe , n_jobs = 1 , param_grid =...scikit-learn.org/stable/auto_examples/compose/plot_compare_reduction.html -
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 -
Replace Splunk with Elastic for Logs, Security ...
visualizations or our lightning fast piped query language to get insights...language ES|QL is Elastic's new piped query language and engine that...www.elastic.co/splunk-replacement -
Categorical Feature Support in Gradient Boostin...
for pipe in ( hist_dropped , hist_one_hot...hist_ordinal , hist_native ): if pipe is hist_native : # The native...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_categorical.html -
Which Movies Popularized (or Tarnished) Baby Na...
the pipes, the pipes are calling." In response,...Dannys are Irishmen who hear the pipes a'callin. Somebody made something...digg.com/stat-significant/link/which-movies-popularized-or-tarnished-baby-names -
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 -
Introducing the set_output API — scikit-learn 1...
transform_output = "pandas" ) num_pipe = make_pipeline ( SimpleImputer...ColumnTransformer ( ( ( "numerical" , num_pipe , num_cols ), ( "categorical"...scikit-learn.org/stable/auto_examples/miscellaneous/plot_set_output.html -
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 -
maxabs_scale — scikit-learn 1.5.0 documentation
most risks of data leaking: pipe = make_pipeline(MaxAbsScaler(),...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html