Root Mean Square Error (RMSE) is a way to measure how far off predictions or estimates are from the actual values. It gives you an idea of the average size of the errors in a set of measurements, but with more focus on larger errors.
Here's how it works:
- Calculate the error: For each prediction, subtract the actual value from the predicted value. This gives you the “error” for each measurement.
- Square the errors: This step removes negative signs and gives more weight to larger errors.
- Find the average of the squared errors: Add up all the squared errors and then divide by the number of measurements. This gives you the “mean” squared error.
- Take the square root: Finally, take the square root of the mean squared error. This brings the result back to the same units as the original values (e.g., meters, degrees).
Why it matters:
RMSE gives you a single number that represents how “off” your predictions are, on average. Lower RMSE means better accuracy, while higher RMSE means larger errors.
