Table 1.

Classification Accuracies Obtained in the Wisconsin Breast Cancer Database With Propositions From the Literature.

Source	Method	Accuracy (%)
Kong et al11	FS and DA	93.85
Quinlan12	DT/LP	94.74
Nauck and Kruse13	FS and NN	95.06
Lee et al14	FS	95.14
Abonyi and Szeifert8	FS	95.57
Verikas and Bacauskiene15	NN	96.44
Setiono16	NN	96.58
Setiono17	NN	96.70
Street et al5	DT/LP	97.30
Peña-Reyes and Sipper18	FS	97.80
Fogel et al6	NN	98.05
Abbass19	NN	98.10
Polat and Günes20	S/SVM	98.53
Albrecht et al21	DT/LP	98.80
Marcano-Cedeño et al7	NN	99.26
Akay2	S/SVM	99.51
Marcano-Cedeño et al9	NN	99.63
Onan10	FT	99.71

Abbreviations: DA, discriminant analysis; DT/LP, Decision Trees/Linear Programming; FS, feature selection; FT, fuzzy theory; NN, neural network; S/SVM, statistics/support vector machine.