What is the primary purpose of applying a Min-Max Scaler to a feature set?
Data ScienceMedium
Data Science — Medium
What is the primary purpose of applying a Min-Max Scaler to a feature set?
Explanation
Min-Max scaling (or normalization) rescales the data so that all feature values fall within a specific range, usually [0, 1]. This is useful for algorithms sensitive to the scale of input features, such as neural networks or distance-based models. It does not remove outliers or change the shape of the distribution.
