Table 2: Confusion matrix of classified results by proposed method based on complex network.

ProjectClass 1Class 2Class 3

Class 1438778
Class 21554670
Class 32306477
Kappa coefficient0.9951
Kappa error0.0007
Maximum Possible Kappa0.9979