Impact of Parameter Tuning for Optimizing Deep Neural Network Models for Predicting Software Faults

Table 3

Comparative results for the KC3 dataset.

KC3
Algorithm	Precision	Recall	F-measure	Accuracy
RF	0.832	0.968	0.895	81.440
DT	0.870	0.930	0.899	82.990
NB	0.863	0.880	0.971	78.870
Without dropout DNN	0.890	0.870	0.880	93.000
With dropout DNN	0.910	1.000	0.980	97.000