Empirical Study of Homogeneous and Heterogeneous Ensemble Models for Software Development Effort Estimation

Table 6

Models’ performance using Miyazaki dataset.

Model type	Model	MMRE	PRED(25)	EF
Individual	MLP	65.86	20.0	0.30
	SVR	108.37	30.0	0.27
	ANFIS	36.18	20.0	0.54
Homogeneous ensemble; (MLP)	HM-MLP-[Avg]	176.62	20.0	0.11
	HM-MLP-[WtAvg]	176.60	20.0	0.11
	HM-MLP-[MLP]	69.23	30.0	0.43
	HM-MLP-[SVR]	107.68	30.0	0.28
	HM-MLP-[FIS-FCM]	317.26	10.0	0.03
	HM-MLP-[FIS-SC]	82.92	40.0	0.48
	HM-MLP-[ANFIS-FCM]	56.14	40.0	0.70
	HM-MLP-[ANFIS-SC]	95.54	10.0	0.10
Homogeneous ensemble; (SVR)	HM-SVR-[Avg]	48.05	30.0	0.61
	HM-SVR-[WtAvg]	49.49	30.0	0.59
	HM-SVR-[MLP]	93.79	40.0	0.42
	HM-SVR-[SVR]	105.06	20.0	0.19
	HM-SVR-[FIS-FCM]	85.07	40.0	0.46
	HM-SVR-[FIS-SC]	39.89	40.0	0.98
	HM-SVR-[ANFIS-FCM]	106.68	30.0	0.28
	HM-SVR-[ANFIS-SC]	35.49	60.0	1.64
Homogeneous ensemble; (ANFIS)	HM-ANFIS-[Avg]	30.74	30.0	0.95
	HM-ANFIS-[WtAvg]	30.74	30.0	0.95
	HM-ANFIS-[MLP]	103.44	30.0	0.29
	HM-ANFIS-[SVR]	114.64	40.0	0.35
	HM-ANFIS-[FIS-FCM]	138.52	20.0	0.14
	HM-ANFIS-[FIS-SC]	171.95	20.0	0.12
	HM-ANFIS-[ANFIS-FCM]	101.49	70.0	0.68
	HM-ANFIS-[ANFIS-SC]	118.47	10.0	0.08
Heterogeneous ensemble; (MLP, SVR, ANFIS)	HT-(MLP, SVR, ANFIS)-[Avg]	58.29	50.0	0.84
	HT-(MLP, SVR, ANFIS)-[WtAvg]	50.84	50.0	0.96
	HT-(MLP, SVR, ANFIS)-[MLP]	83.82	60.0	0.71
	HT-(MLP, SVR, ANFIS)-[SVR]	114.18	30.0	0.26
	HT-(MLP, SVR, ANFIS)-[FIS-FCM]	130.00	20.0	0.15
	HT-(MLP, SVR, ANFIS)-[FIS-SC]	78.71	30.0	0.38
	HT-(MLP, SVR, ANFIS)-[ANFIS-FCM]	149.92	20.0	0.13
	HT-(MLP, SVR, ANFIS)-[ANFIS-SC]	64.95	30.0	0.45