Research Article
Ensemble Merit Merge Feature Selection for Enhanced Multinomial Classification in Alzheimer’s Dementia
Table 5
Description of the J48 ensemble model used for the multiclass classification.
| Details | Value |
| Split method | Binary split |
| Cross validation accuracy | 0.976 |
| AUC with CV | 0.971 |
| Train and test accuracy | 0.986 |
| AUC with train and test | 0.987 |
| Common features selected by all methods | MMSE, CDR, hippocampus volume, and everyday cognition measures |
| Features added by CPEMM | Entorhinal measures, CDRSB, and Ray Auditory Verbal Learning Test-immediate |
|
|