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Table 2 Accuracy of fuzzy support vector machine model versus accuracy of common classification models used on microarrays when no feature selection step is taken.

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

 

Leukemia

Prostate Cancer

Colon Cancer

Fuzzy Support Vector Machine (FSVM)

90.18 %

91.18 %

77.42%

Support Vector Machine (SVM)

94.36 %

93.55 %

80.70%

Artificial Neural Network (ANN)

76.81 %

81.09 %

75.80%

Decision Tree (CART)

69.63 %

73 %

69.35%

K Nearest Neighbor (KNN, K = 3)

94.18 %

93.27 %

72.58%

Diagonal Linear Discriminant Analysis (DLDA)

95.27 %

94.27 %

75.80%