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Table 9 The discriminating axes. The discriminating axes that accounted for the optimum accuracy in 1 to 3-feature model classifier.

From: Classification between normal and tumor tissues based on the pair-wise gene expression ratio

Order or classifier Optimum Accuracy* / % Discriminating axes Order or classifier Optimum Accuracy* / % Discriminating axes
1 87.10% #1659 1 93.55% #1831/#1537
2 91.94% (#241)&(#1659) 2 98.39% (#753/#768) & (#1831/#1537)
3 95.16% (#241)&(#1659)&(#1759) 3 98.39% (#753/#768) & (#1831/#1537)&(#481/#1394)
Prostate cancer–Original expression data Prostate cancer–Transformed expression data
Order or classifier Optimum Accuracy* / % Discriminating axes Order or classifier Optimum Accuracy* / % Discriminating axes
1 86.27% (#6185) 1 84.62% (#6185/#5840)
2 100.00% (#6185)&(#9850) 2 100.00% (#6185/#5840)&(#6185/#6749)
3 100.00% (#6185)&(#9850)&(#12148) 3 100.00% (#6185/#5840)&(#6185/#6749)&(#7247/#7067)
  1. * : best accuracy based on the specified number of gene/gene ratio as discriminating axes ****Please do not delete from here on, needed for the correct order of reference list****** [32-54]