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)