Mean-absolute error at a glance

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• Description: Mean of absolute 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 timeframe
• Metrics details available: None

Do the math

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The Mean absolute error is calculated by adding up all the absolute errors and dividing them by the number of errors.

                         SUM  | Yi - Xi | 
Mean absolute errors =  ____________________

                          number of errors
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Learn more

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Reviewing quality results

Parent topic: Quality metrics overview