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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 -
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 -
6.1. Pipelines and composite estimators — sciki...
SVC ())] >>> pipe = Pipeline ( estimators ) >>> pipe Pipeline(s...pipeline: >>> pipe . steps [ 0 ] ('reduce_dim', PCA()) >>> pipe [ 0 ]...scikit-learn.org/stable/modules/compose.html -
Balance model complexity and cross-validated sc...
argmin () ] return best_idx pipe = Pipeline ( [ ( "reduce_dim"...14 ]} grid = GridSearchCV ( pipe , cv = 10 , n_jobs = 1 , param_grid...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_refit_callable.html -
Comparing Target Encoder with Other Encoders — ...
pipe ): result = cross_validate ( pipe , X , y , scoring...categorical_features ), ] ) pipe = make_pipeline ( preprocessor...scikit-learn.org/stable/auto_examples/preprocessing/plot_target_encoder.html -
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 -
Displaying Pipelines — scikit-learn 1.4.2 docum...
] pipe = Pipeline ( steps ) pipe # click on the...= "linear" ))] pipe = Pipeline ( steps ) pipe # click on the...scikit-learn.org/stable/auto_examples/miscellaneous/plot_pipeline_display.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 -
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 -
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