Recognition of Multiple Imbalanced Cancer Types Based on DNA Microarray Data Using Ensemble Classifiers

Table 4

𝐹-score of various classification methods on eight datasets, where bold represents the best result, underline denotes the second best, and italic labels the worst one in each column, respectively.

Methods	Brain_Tumor1	Brain_Tumor2	Leukemia1	Leukemia2	Lung_Cancer	SRBCT	11_Tumors	14_Tumors
SVM-OAA	0.6524	0.6358	0.9542	0.9328	0.9068	0.9994	0.8468	0.4799
SVM-OAO	0.6732	0.6302	0.9430	0.9315	0.8976	0.9842	0.8322	0.4581
SVM-DDAG	0.6459	0.6420	0.9297	0.9162	0.8762	0.9976	0.8106	0.4564
SVM-ECOC	0.6538	0.6286	0.9418	0.9473	0.9018	0.9902	0.8528	0.4632
SVM-OAA(THR)	0.6251	0.6845	0.8665	0.9602	0.8621	0.9804	0.8453	0.5096
SVM-OAA(RUS)	0.6832	0.6732	0.9352	0.9559	0.9062	0.9992	0.8569	0.5124
EnSVM-OAA	0.6458	0.6437	0.9598	0.9437	0.8975	1.0000	0.8664	0.4907
MCSVM	0.6726	0.6388	0.9562	0.9306	0.9011	0.9782	0.8229	0.4752
Ramp-MCSVM	0.6918	0.7032	0.9478	0.9375	0.9128	0.9718	0.8776	0.4948
AdaBoost.NC	0.7014	0.6959	0.9724	0.9596	0.9216	1.0000	0.8456	0.4749
EnSVM-OAA(THR)	0.6325	0.7448	0.9457	0.9774	0.9022	0.9924	0.8768	0.5869
EnSVM-OAA(RUS)	0.7345	0.7029	0.9648	0.9617	0.9214	1.0000	0.8952	0.5637