Data Science, Machine Learning, Regression, Evaluation Metric, Linear Regression.
The Mean Squared Error (MSE) places a higher penalty on larger errors compared to the MAE. By squaring the errors, the MSE score amplifies the impact of these errors, which makes it more suitable for situations where larger errors should be heavily penalized. The main drawback of the MSE score,