Python sklearn.model_selection Module

This page shows the popular functions and classes defined in the sklearn.model_selection module. The items are ordered by their popularity in 40,000 open source Python projects. If you can not find a good example below, you can try the search function to search modules.

• 1. train_test_split()    
  Used in 670 projects
• 2. KFold()    
  Used in 204 projects
• 3. GridSearchCV()    
  Used in 167 projects
• 4. StratifiedKFold()    
  Used in 152 projects
• 5. cross_val_score()    
  Used in 112 projects
• 6. RandomizedSearchCV()    
  Used in 42 projects
• 7. ShuffleSplit()    
  Used in 42 projects
• 8. StratifiedShuffleSplit()    
  Used in 40 projects
• 9. ParameterGrid()    
  Used in 32 projects
• 10. cross_val_predict()    
  Used in 23 projects
• 11. GroupKFold()    
  Used in 21 projects
• 12. learning_curve()    
  Used in 19 projects
• 13. cross_validate()    
  Used in 16 projects
• 14. ParameterSampler()    
  Used in 15 projects
• 15. check_cv()    
  Used in 15 projects
• 16. LeaveOneOut()    
  Used in 13 projects
• 17. TimeSeriesSplit()    
  Used in 12 projects
• 18. RepeatedStratifiedKFold()    
  Used in 10 projects
• 19. BaseCrossValidator()    
  Used in 9 projects
• 20. GroupShuffleSplit()    
  Used in 9 projects
• 21. LeaveOneGroupOut()    
  Used in 9 projects
• 22. validation_curve()    
  Used in 8 projects
• 23. RepeatedKFold()    
  Used in 7 projects
• 24. PredefinedSplit()    
  Used in 6 projects
• 25. LeavePGroupsOut()    
  Used in 6 projects
• 26. LeavePOut()    
  Used in 5 projects