Explore how feature engineering aids in normalizing varying numeric feature scales for cohesive model training. Learn how scaling through feature engineering enhances machine learning model performance.
Table of Contents
Question
You need to train and test your ML model. You prepare data for model training. Several of your numeric features have different scales: the first feature has a minimum value of 0.253 and a max of 0.987, the second one – from 12 to 124, and the last one – from 13545 to 56798. You need to bring them to a common scale.
You decide to use feature engineering to address this problem.
Does this decision help you to achieve your goal?
A. Yes
B. No
Answer
B. No
Explanation
You need to normalize your numeric features. The process of normalization brings numeric features to a common scale.
Feature engineering is the method of creating new features based on the existing ones.
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