Software Defect Prediction through Neural Network and Feature Selections

Table 8

Comparison of RBF results with other previous methods before feature selection for KC1 data set.

Source	Algorithm	F-measure	Accuracy
[3]	MLP	N/A	79.46%
[47]	Naive Bayes	0.90	82.10%
	MLP	0.92	85.51%
	SVM	0.92	84.47%
	RBF	0.92	84.99%
[42]	J48	N/A	84.63%
[48]
	This research	RBF	0.83	83.25