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Table 3 Accuracy of fuzzy support vector machine model versus accuracy of common classification models used on microarrays when SNR is used for feature selection

From: Fuzzy support vector machine: an efficient rule-based classification technique for microarrays

 

Leukemia

Prostate Cancer

Colon Cancer

Fuzzy Support Vector Machine (FSVM)

98.57 %

95.18 %

93.75%

Support Vector Machine (SVM)

97.27 %

93.63 %

90.03%

Artificial Neural Network (ANN)

94.54 %

94.27 %

87.10%

Decision Tree (CART)

91.81 %

89.09 %

83.87%

K Nearest Neighbor (KNN, K = 3)

96.36 %

95.18 %

87.10%

Diagonal Linear Discriminant Analysis (DLDA)

96.18 %

94 %

88.71%