Mean or median imputation with Feature-engine
Learn how to perform mean or median imputation with the open source package Feature-engine. Mean or median imputation consists in replacing missing values in numerical variables by the mean or median value of the variable. With the MeanMedianImputer from Feature-engine, we can do exactly that in a few lines of code. The mean median imputer will automatically select all numerical variables in the dataset. Alternatively, the user can indicate which variables to impute. The Mean Median imputer will learn the mean or median from the variables and store the values when we use the fit method. With the transform method, the imputer will impute missing data with the learn parameters.
Feature-engine can be used within a Scikit-learn pipeline, making model deployment as well as model training and prediction making very straightforward.
To learn more about Feature-engine visit:
https://www.trainindata.com/feature-e...
https://feature-engine.readthedocs.io...
To learn more about Feature Engineering visit:
https://www.udemy.com/feature-enginee...