- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 11 - 20 of 132 for pipe (0.22 sec)
-
sklearn.preprocessing.quantile_transform — scik...
scikit-learn.org/stable/modules/generated/sklearn.preprocessing.quantile_transform.html -
sklearn.pipeline.Pipeline — scikit-learn 1.4.2 ...
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 -
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 -
Navigating the web of Scattered Spider: Defendi...
iteratively: Elastic’s new piped query language ES|QL (Elasticsearch...target with each successive pipe, changing how they pursue threats...www.elastic.co/blog/scattered-spider-cybercriminal-networks -
Culture & Trends: Latest News, Photos and Video...
www.nbcnews.com/culture-matters -
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 -
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 -
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 -
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 -
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