Research Article
Detecting Shilling Attacks with Automatic Features from Multiple Views
Algorithm 3
Detection.
| Input: DRtrain, DRtest, SDAEopts, Lcrate, UcrateSetmd, Setfs, Setas | |
| Output: Ylabels | |
| 1for i=Lcrate to Ucrate do | |
| 2Featraini=FeaExtra(Setmd, Setfs, Setas, DRtrain,i) | |
| 3Feateseti=FeaExtra(Setmd, Setfs, Setas, DRtest,i) | |
| 4Ylabel(i)=fSVM(Feataini,DRtrain,DRtest) | |
| 5end for | |
| 6Ylabels=voteLabel(Ylabel) | |
| 7Return Ylabels |