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Table 3 Average classification accuracy over 100 runs on data obtained by grouping all control and BPH samples into one class, and all cancer samples into another. Class sizes thus remain approximately balanced. Numbers in parentheses are standard deviations.

From: Computational protein biomarker prediction: a case study for prostate cancer

  # of peaks used (malignant vs. other)
  5 8 10 12 15
Quadr. Disc. 84.1 (5.3) 85.1 (5.4) 85.0 (6.1) 86.1 (6.7) 86.0 (6.1)
Nonpar. (Kernel) 84.6 (5.2) 87.1 (5.3) 88.3 (5.8) 88.9 (6.1) 88.1 (6.0)
kNN 89.9 (4.6) 87.4 (5.6) 87.5 (5.7) 88.9 (5.2) 88.5 (4.6)
Fisher Linear 88.6 (5.9) 88.4 (5.6) 87.9 (4.9) 89.1 (5.4) 88.0 (5.0)
Linear SVM 89.5 (5.5) 91.0 (4.8) 91.9 (4.6) 91.7 (4.9) 91.9 (4.7)