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Table 1 Cross-validation classification accuracy (in percent) of various classification methods on the full four-class prostate cancer dataset using various numbers of peaks. Numbers are average observed accuracies over 100 runs with randomized 90/10 splits into training and test sets, respectively. The numbers in parentheses are the corresponding standard deviations.

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

  # of peaks used
  10 15 20 25 30 35 50 70
Quadr. Discr. 74.7 (7.4) 74.7 (9.6) 74.1 (8.4) 74.7 (7.1) 78.2 (6.8) 77.8 (7.3) 78.7 (6.6) 76.8 (7.1)
Nonpar (Kernel) 76.7 (7.1) 77.4 (8.4) 77.7 (6.9) 78.6 (6.6) 80.0 (6.3) 79.9 (7.3) 78.1 (6.5) 76.1 (7.6)
kNN 73.4 (7.4) 76.4 (6.9) 76.9 (6.0) 76.6 (6.1) 75.8 (6.7) 77.2 (6.9) 73.9 (7.5) 69.8 (6.7)
Fisher Linear 72.4 (7.3) 77.3 (6.9) 80.8 (6.5) 80.1 (5.8) 81.8 (6.0) 84.6 (5.2) 85.5 (6.1) 84.3 (5.1)
Linear SVM 75.4 (6.4) 79.3 (7.4) 81.7 (7.2) 81.3 (5.7) 83.7 (6.8) 83.1 (6.6) 83.5 (6.1) 84.0 (6.2)