|
Average ROC and ROC50 scores
|
|---|
|
Methods
|
ROC
|
ROC50
|
Source
|
|
SVM-Top-n-gram
| | | |
|
n = 1
|
0.7778
|
0.649
| |
|
n = 2
|
0.8130
|
0.642
| |
|
n = 3
|
0.7960
|
0.628
| |
|
SVM-Top-n-gram-combine
|
0.8180
|
0.677
| |
|
SVM-Bprofile(Ph = 0.11)
|
0.8042
|
0.644
| |
|
SVM-Top-n-gram-combine-LSA
|
0.8535
|
0.694
| |
|
SVM-Bprofile-LSA(Ph = 0.11)
|
0.8233
|
0.658
| |
|
PSI-BLAST
|
0.5010
|
0.010
|
[24]
|
|
SVM-Pairwise
|
0.7240
|
0.359
|
[24]
|
|
SVM-LA
|
0.8340
|
0.504
|
[24]
|
|
Gpkernel
|
0.8440
|
0.514
|
[24]
|
|
Mismatch
|
0.8140
|
0.467
|
[24]
|
|
eMOTIF
|
0.6980
|
0.308
|
[24]
|
- SVM-Bprofile and SVM-Top-n-gram refer to the methods based on the two building blocks: binary profiles and Top-n-grams respectively. The methods with combine suffix refer to the methods combining Top-1-grams and Top-2-grams. The methods with LSA suffix refer to the corresponding methods after latent semantic analysis. The results of the methods based on binary profiles were obtained by running the implementation of our previous work.
