Table 20 Stacking and blending ensemble classifiers error metrics result on NYSE 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 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1.232 | 0.034 |
STK_SND_C | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 2.28 | 0.062 |
STK_DNS_C | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1.373 | 0.045 |
Vote(DSN) | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 3.182 | 0.077 |
BLD_DSN_C | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 6.17 | 0.293 |
BLD_SND_C | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 7.377 | 0.373 |
BLD_DNS_C | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 8.157 | 0.383 |