Root Mean Square Error (RMSE)

Root Mean Square Error (RMSE) is a way to measure how accurately a model's predictions match actual data. It calculates the average difference between predicted and real values, emphasizing larger errors by squaring them. After averaging these squared errors, the square root is taken to bring the result back to the original units. A lower RMSE indicates that the model's predictions are closer to the actual data, reflecting better accuracy. It's a useful tool for evaluating and comparing the performance of predictive models across different datasets or scenarios.