Python sklearn Module

This page shows the popular functions and classes defined in the sklearn 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. metrics()    
  Used in 81 projects
• 2. __version__()    
  Used in 60 projects
• 3. model_selection()    
  Used in 55 projects
• 4. preprocessing()    
  Used in 49 projects
• 5. datasets()    
  Used in 46 projects
• 6. linear_model()    
  Used in 42 projects
• 7. svm()    
  Used in 37 projects
• 8. cluster()    
  Used in 36 projects
• 9. ensemble()    
  Used in 35 projects
• 10. neighbors()    
  Used in 27 projects
• 11. decomposition()    
  Used in 23 projects
• 12. base()    
  Used in 22 projects
• 13. utils()    
  Used in 19 projects
• 14. tree()    
  Used in 16 projects
• 15. pipeline()    
  Used in 15 projects
• 16. externals()    
  Used in 11 projects
• 17. neural_network()    
  Used in 11 projects
• 18. cross_validation()    
  Used in 10 projects
• 19. naive_bayes()    
  Used in 10 projects
• 20. feature_selection()    
  Used in 10 projects
• 21. mixture()    
  Used in 8 projects
• 22. exceptions()    
  Used in 8 projects
• 23. clone()    
  Used in 8 projects
• 24. manifold()    
  Used in 7 projects
• 25. grid_search()    
  Used in 5 projects
• 26. discriminant_analysis()    
  Used in 5 projects
• 27. impute()    
  Used in 5 projects