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Table 3 kNN approach: The error rates according to the number of genes. The sets of Ogawa (OS, [26]) and Gasch (GS, GSHEAT and GSH2O2, [25]) have been cut into subsets representing from (1/2) to (1/7) of the original sets. For each of the subsets, the optimal value for k (k opt ), i.e. the number of neighbours used in kNN approach, has been computed. It was chosen as the number which minimizes the error rate. In regards to each subset is given the number of genes (nb genes).

From: Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering

  OS GS GSHEAT GSH2O2
subsets nb genes error rate k opt nb genes error rate k opt nb genes error rate k opt nb genes error rate k opt
(1/7) 827 0.190 14 815 0.292 18 523 0.183 12 717 0.143 14
(1/6) 968 0.186 20 955 0.276 8 608 0.199 15 837 0.155 11
(1/5) 1159 0.187 20 1141 0.283 23 731 0.195 22 1003 0.155 17
(1/4) 1448 0.180 22 1427 0.270 26 913 0.199 28 1254 0.146 13
(1/3) 1929 0.180 23 1903 0.274 8 1215 0.187 23 1669 0.139 15
(1/2) 2892 0.174 30 2853 0.255 7 1822 0.187 8 2504 0.135 16
set 5783 0.177 39 5705 0.255 8 3643 0.186 10 5007 0.135 17