Root of mean squared error
The root-mean-squared error (RMSE) view shows the difference between the predicted and observed values in your model.
Root of mean squared error at a glance
- Description: Square root of mean of squared difference between model prediction and target value
- Default thresholds: Upper limit = 80%
- Default recommendation:
- Upward trend: An upward trend indicates that the metric is deteriorating. Feedback data is becoming significantly different than the training data.
- Downward trend: A downward trend indicates that the metric is improving. This means that model retraining is effective.
- Erratic or irregular variation: An erratic or irregular variation indicates that the feedback data is not consistent between evaluations. Increase the minimum sample size for the Quality monitor.
- Problem type: Regression
- Chart values: Last value in the time frame
- Metrics details available: None
Do the math
The Root of mean squared error is equal to the Square root of the mean of (forecasts minus observed values) squared.
___________________________________________________________ RMSE = √(forecasts - observed values)*(forecasts - observed values)