Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble

Table 4

-score of different classification methods.

Datasets	NervSys	Leukemia	DLBCL1	DLBCL2	DLBCL3	Prostate	Ovarian	Lung1	Lung2
CSNB stacking	0.900	1.00	1.00	0.987	0.878	0.951	1.00	0.989	1.00
CSKNN stacking	0.829	1.00	1.00	0.987	0.844	0.922	1.00	0.989	1.00
CSC4.5 stacking	0.899	1.00	1.00	0.987	0.861	0.931	1.00	0.945	0.995
CSLIBSVM stacking	0.869	1.00	1.00	0.974	0.775	0.922	1.00	0.909	0.995
Bagging	0.829	1.00	1.00	0.974	0.842	0.931	1.00	0.989	1.00
AdaBoost	0.813	1.00	1.00	0.961	0.844	0.951	1.00	0.989	1.00
CSNB	0.767	1.00	1.00	0.961	0.862	0.922	1.00	0.989	1.00
NB	0.767	1.00	1.00	0.961	0.862	0.922	1.00	0.989	1.00
LIBSVM	0.867	1.00	1.00	0.987	0.821	0.941	1.00	0.989	0.995
KNN	0.869	1.00	0.957	0.937	0.707	0.892	1.00	0.989	1.00
RF	0.879	0.986	1.00	0.960	0.860	0.941	0.996	0.989	0.994
C4.5	0.741	0.822	0.785	0.838	0.724	0.882	0.980	0.952	0.955