Standardization vs Normalization

Oftentimes, the input features in our data can have different units of measurement. As a result, each feature can have its own unique distribution of values. Unfortunately, incorporating features with different distributions can lead to a model showing bias towards features with larger values and variance. Feature scaling addresses this issue by fitting all data to a specific scale, which is why it is often a necessary component in feature engineering. The two most common methods of feature scaling are standardization and normalization.