What is the impact of feature scaling on machine learning performance?

What is the impact of feature scaling on machine learning performance?

Feature scaling can significantly affect the performance of machine learning algorithms, especially those that rely on distance calculations, like k-NN or SVM.

Can you explain why algorithms like k-NN are sensitive to feature scaling?

Sure! k-NN uses distance metrics to determine the closest neighbors, so if features are on different scales, the algorithm may be biased towards features with larger ranges.

What are some common methods for feature scaling?

Common methods include Min-Max scaling, Standardization (Z-score normalization), and Robust scaling, each serving different purposes.

When should I use Min-Max scaling over Standardization?

Use Min-Max scaling when you want to bound your features within a specific range, while Standardization is better when your data follows a Gaussian distribution.