Research Article

Software Defect Prediction for Healthcare Big Data: An Empirical Evaluation of Machine Learning Techniques

Table 9

Comparative analysis of RAE.

S. No.TechniqueAR1AR3CM1JM1KC2KC3MC1

1SVM57.24947.90858.37960.938852.777559.231349.9624
2J4887.976969.24898.213285.902172.67577.887769.4547
3RF87.961163.436891.194582.753267.492984.379257.6946
4MLP71.826647.461187.648285.755969.13577.852149.9963
5RBF107.817578.1281100.97492.575373.310398.3279174.0763
6HMM346.3562215.586279.5455166.9291153.0549164.15533477.5284
7CDT95.475290.103797.589387.912170.2991.981978.072
8A1DE108.746543.7714105.430586.513860.388.8947179.4312
9NB105.24946.768685.221862.213950.147170.9899410.217
10KNN72.315166.84686.636477.431164.709592.20944.0253

The bold values in the table indicate the reduced error rate.