root mean square error

Root Mean Square Error (RMSE) is a metric used to measure how accurately a model's predictions match actual observed data. It calculates the average of the squared differences between predicted and actual values, then takes the square root of that average. RMSE provides a single number indicating the typical size of prediction errors—lower values mean the model's predictions are closer to real data, while higher values suggest less accuracy. It is widely used because it emphasizes larger errors more than smaller ones, helping to identify models that perform well overall.