Table 18 Stacking and blending ensemble classifiers error metrics result over BSE dataset
From: A comprehensive evaluation of ensemble learning for stock-market prediction
Model | Mean | STD | RMSE | MAE | R2 | Precision | Recall | AUC | Train time | Test time |
|---|---|---|---|---|---|---|---|---|---|---|
STK_DSN_C | 1.000 | 0.000 | 0 | 0 | 1 | 1 | 1 | 1 | 1.044 | 0.028 |
STK_SND_C | 0.989 | 0.013 | 0 | 0 | 1 | 1 | 1 | 1 | 1.922 | 0.109 |
STK_DNS_C | 0.995 | 0.009 | 0 | 0 | 1 | 1 | 1 | 1 | 1.009 | 0.073 |
Vote(DSN) | 0.992 | 0.011 | 0 | 0 | 1 | 1 | 1 | 1 | 1.634 | 0.058 |
BLD_DSN_C | 1.000 | 0.000 | 0 | 0 | 1 | 1 | 1 | 1 | 5.408 | 0.389 |
BLD_SND_C | 0.980 | 0.016 | 0 | 0 | 1 | 1 | 1 | 1 | 7.323 | 0.388 |
BLD_DNS_C | 1.000 | 0.000 | 0 | 0 | 1 | 1 | 1 | 1 | 6.882 | 1.341 |