Feature Engineering Made Easy

Custom imputers

 Before we jump into the code, let's have a quick refresher of pipelines:

• Pipelines allow us to sequentially apply a list of transforms and a final estimator
• Intermediate steps of the pipeline must be transforms, meaning they must implement fit and transform methods
• The final estimator only needs to implement fit

The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. Once we have built our custom transformers for each column that needs imputing, we will pass them all through a pipeline so that our data can be transformed in one go. Let's build our custom category imputer to start.