In the over view of Auto Model, there is Error and Standard Deviation.
The description of performance in the information is;
"Performance: lists the model's prediction accuracy and other performance criteria, depending on the type of classification problem. The performance is calculated on a 40% hold out set which has not been used for any of the performed model optimizations. This hold-out set is then used as input for a multi-hold-out-set validation where we calculate the performance for 7 disjoint subsets. The largest and the highest performance are removed and the average of the remaining 5 performances is reported here. Although this validation is not as thorough as a full cross-validation, this approach strikes a good balance between runtime and model validation quality."
I think it is the standard deviation of the remaining 5 performances. Am I correct?
Regards,
Koichi
