Python sklearn.preprocessing Module

This page shows the popular functions and classes defined in the sklearn.preprocessing 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. StandardScaler()    
  Used in 382 projects
• 2. LabelEncoder()    
  Used in 232 projects
• 3. MinMaxScaler()    
  Used in 228 projects
• 4. normalize()    
  Used in 156 projects
• 5. OneHotEncoder()    
  Used in 113 projects
• 6. scale()    
  Used in 107 projects
• 7. LabelBinarizer()    
  Used in 80 projects
• 8. PolynomialFeatures()    
  Used in 55 projects
• 9. Imputer()    
  Used in 44 projects
• 10. MultiLabelBinarizer()    
  Used in 43 projects
• 11. Normalizer()    
  Used in 41 projects
• 12. RobustScaler()    
  Used in 32 projects
• 13. label_binarize()    
  Used in 26 projects
• 14. FunctionTransformer()    
  Used in 23 projects
• 15. MaxAbsScaler()    
  Used in 16 projects
• 16. minmax_scale()    
  Used in 15 projects
• 17. Binarizer()    
  Used in 10 projects
• 18. QuantileTransformer()    
  Used in 10 projects
• 19. OrdinalEncoder()    
  Used in 10 projects
• 20. binarize()    
  Used in 8 projects
• 21. KBinsDiscretizer()    
  Used in 6 projects
• 22. PowerTransformer()    
  Used in 5 projects
• 23. robust_scale()    
  Used in 5 projects