Stop Guessing AI Metrics: Regression Explained with MSE, RMSE, MAE, R² & MAPE

Regression in machine learning predicts numbers, not categories.To evaluate such models, common metrics are used: MSE and RMSE penalize large errors, MAE shows the average absolute error, R-squared explains how well the model fits the data, and MAPE expresses error as a percentage. Each metric has its strengths, and the right choice depends on whether you care more about interpretability, outliers, or large mistakes.