Comparison Of Huber Loss Vs. MSE And MAE

Here is a graphical representation comparing Huber Loss, Mean Squared Error (MSE), and Mean Absolute Error (MAE):

• Green Line (Huber Loss): Shows how Huber Loss behaves quadratically for small residuals (like MSE) but switches to a linear approach (like MAE) for larger residuals. This helps minimize the impact of outliers.
• Orange Dashed Line (MSE): Penalizes large residuals more heavily because of the quadratic increase, making it sensitive to outliers.
• Purple Dot-Dashed Line (MAE): Applies a linear penalty to all residuals, reducing the impact of outliers but less smooth for optimization.

Dataset:

• Inliers (Most Houses): (1200 sq. ft, $300K), (1500 sq. ft, $350K), (1800 sq. ft, $400K)
• Outliers (Luxury Mansion): (2000 sq. ft, $2M)

The plot illustrates how Huber Loss effectively balances the behavior of MSE and MAE, making it robust in scenarios with outliers, such as the luxury mansion example.