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Exercise

Kidney disease case study II: Feature Union

Having separately imputed numeric as well as categorical columns, your task is now to use scikit-learn's FeatureUnion to concatenate their results, which are contained in two separate transformer objects - numeric_imputation_mapper, and categorical_imputation_mapper, respectively.

You may have already encountered FeatureUnion in Machine Learning with the Experts: School Budgets. Just like with pipelines, you have to pass it a list of (string, transformer) tuples, where the first half of each tuple is the name of the transformer.

Instructions

100 XP
  • Import FeatureUnion from sklearn.pipeline.
  • Combine the results of numeric_imputation_mapper and categorical_imputation_mapper using FeatureUnion(), with the names "num_mapper" and "cat_mapper" respectively.