Table 7.
Weighted BER | Complete features | Imputed features | Average |
---|---|---|---|
dLDA | 0.172 | 0.216 | 0.194 |
SVM-lin | 0.276 | 0.242 | 0.259 |
SVM-poly | 0.285 | 0.334 | 0.310 |
SVM-rbf | 0.493 | 0.520 | 0.507 |
SVM-mlp | 0.136 | 0.352 | 0.244 |
Bayesian LSSVM | 0.371 | 0.469 | 0.420 |
LSSVM-lin | 0.452 | 0.280 | 0.366 |
LSSVM-poly | 0.462 | 0.362 | 0.412 |
LSSVM-rbf | 0.408 | 0.320 | 0.364 |
Random forests | 0.148 | 0.294 | 0.221 |
AdaBoost | 0.505 | 0.324 | 0.415 |
LogitBoost | 0.148 | 0.335 | 0.242 |
GentleBoost | 0.296 | 0.308 | 0.302 |
RobustBoost | 0.148 | 0.325 | 0.237 |
LPBoost | 0.505 | 0.256 | 0.381 |
TotalBoost | 0.505 | 0.289 | 0.397 |
RUSBoost | 0.281 | 0.308 | 0.295 |
Classification tree | 0.268 | 0.346 | 0.307 |
3-NN (correlation) | 0.357 | 0.428 | 0.392 |
Pattern net | 0.449 | 0.288 | 0.366 |
Feed forward net | 0.399 | 0.411 | 0.405 |
Cascade forward net | 0.586 | 0.485 | 0.535 |
Fit net | 0.535 | 0.350 | 0.443 |
LDS | 0.442 | 0.534 | 0.488 |
SMIR | 0.278 | 0.436 | 0.357 |
S4VM | 0.456 | 0.473 | 0.465 |