4- Data Scaling 102: Beyond the Basics, Exploring RobustScaler, MaxAbsScaler and Other Scaling Methods

posted on 20 Dec 2024

Scaling is an important step in preparing data for machine learning, which ensures that all features contribute equally to the performance of the model. In my previous article, Data Scaling 101: StandardScaler vs MinMaxScaler, we have seen why scaling matters and compared two popular methods. But is scaling really just about StandardScaler and MinMaxScaler?

No! Though these two are commonly used, they may not be the best for your dataset. In this article, we will go beyond the basics and explore other powerful scaling methods like RobustScaler and MaxAbsScaler that will help us better handle complex datasets for more reliable model performance. Let’s dive deeper into the world of scaling!

To read the full version of this article, which has published on DataDrivenInvestor publication, use the link below:

Data Scaling 102 on Medium