Error Mean
Mean of the differences between predictions and actual values.
The Error Mean or Standard Error of the Mean quantifies the precision of the predictive model's estimations. It's used to determine how precisely the mean of the predictive model's predicted values estimates the population mean.
How to interpret the indicator?
A mean of zero indicates that the mean of the predictive model is the same as the actual data. A mean value close to 0 is better.
A negative mean value indicates that the predictive model always underestimates the values, and often generates values under the actual values.
A high mean value indicates that the predictive model over-estimates the target values, and often generates values above the actual values.
To improve the accuracy of your predictive model, you can bring additional influencers that make the target clearer to the training data source.