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Exercise

Arithmetical features

To practice creating new features, you will be working with a subsample from the Kaggle competition called "House Prices: Advanced Regression Techniques". The goal of this competition is to predict the price of the house based on its properties. It's a regression problem with Root Mean Squared Error as an evaluation metric.

Your goal is to create new features and determine whether they improve your validation score. To get the validation score from 5-fold cross-validation, you're given the get_kfold_rmse() function. Use it with the train DataFrame, available in your workspace, as an argument.

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  • Create a new feature representing the total area (basement, 1st and 2nd floors) of the house. The columns "TotalBsmtSF", "FirstFlrSF" and "SecondFlrSF" give the areas of the basement, 1st and 2nd floors, respectively.
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