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Ejercicio

Preprocess

Feature engineering time! You need to build a recipe to take care of non-informative but possibly valuable variables such as observation ID or deal with missing values. This is also an opportunity to transform some predictors. Say, normalize numerical features and create dummy variables for categorical ones.

The attrition dataset and the train and test splits you created in the previous exercise are available in your environment.

Instrucciones

100 XP
  • Normalize all numeric features.
  • Impute missing values using the knn imputation algorithm.
  • Create dummy variables for all nominal predictors.