What is feature scaling and why is it critical for distance-based models?

Feature scaling ensures all features contribute equally in distance-based algorithms.

Algorithms like KNN, SVM, and KMeans rely on distance calculations. Without scaling, features with larger numeric ranges dominate the distance metric. Standardization or normalization ensures fair contribution of each feature and improves convergence in gradient-based models.