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Getting Started — scikit-learn 1.7.0 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 -
ES|QL | Elastic Docs
Query Language (ES|QL) is a piped query language for filtering,...How does it work? ES|QL uses pipes ( | ) to manipulate and transform...www.elastic.co/docs/explore-analyze/query-filter/languages/esql -
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 -
Logstash Reference [8.18] | 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/8.18/index.html -
ES|QL - Elasticsearch Labs
www.elastic.co/search-labs/blog/category/esql -
4. Metadata Routing — scikit-learn 1.7.0 docume...
= SelectKBest ( k = 2 ) >>> pipe = make_pipeline ( sel , lr )...cv_results = cross_validate ( ... pipe , ... X , ... y , ... cv = GroupKFold...scikit-learn.org/stable/metadata_routing.html -
maxabs_scale — scikit-learn 1.7.0 documentation
most risks of data leaking: pipe = make_pipeline(MaxAbsScaler(),...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html -
Pipeline — scikit-learn 1.7.0 documentation
random_state = 0 ) >>> pipe = Pipeline ([( 'scaler' , StandardScaler...test set into the train set >>> pipe . fit ( X_train , y_train )...scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html -
scale — scikit-learn 1.7.0 documentation
most risks of data leaking: pipe = make_pipeline(StandardScaler(),...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.scale.html -
power_transform — scikit-learn 1.7.0 documentation
: pipe = make_pipeline(PowerTransformer(),...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.power_transform.html