Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

Table 8

Classification accuracies obtained by our method and other classifiers for the hepatitis dataset.

Author (year)	Method	Classification accuracy (%)
Polat and Güneş (2006) [1]	FS-AIRS with fuzzy res. (10-fold CV)	92.59
Polat and Güneş (2007) [2]	FS-Fuzzy-AIRS (10-fold CV)	94.12
Polat and Güneş (2007) [3]	AIRS (10-fold CV)	76.00
	PCA-AIRS (10-fold CV)	94.12
Kahramanli and Allahverdi (2009) [4]	Hybrid system (ANN and AIS) (without k-fold CV)	96.8
Dogantekin et al. (2009) [5]	LDA-ANFIS	94.16
Bascil and Temurtas (2011) [6]	MLNN (MLP) + LM (10-fold CV)	91.87
Our study	ABCFS + SVM (10-fold CV)	94.92