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Table 6 The minimum error rates yielded by Support Vector Machine classifier with feature selection methods along‐with the classification error without selection

From: A feature selection method for classification within functional genomics experiments based on the proportional overlapping score

Dataset

ISIS

Wil‐RS

mRMR

MP

POS

Full set

Leukaemia

0.018 (1)

0.047 (8)

0.126 (50)

0.022 (1)

0.005 (1)

0.131

Breast

0.409 (4)

0.401 (39)

0.407 (50)

0.359 (21)

0.313 (22)

0.438

Srbct

0.106 (2.63)

0.131 (50)

0.124 (49)

0.010 (21)

0.003 (8)

0.079

Lung

0.013 (3.26)

0.066 (50)

0.026 (50)

0.021 (19)

0.010 (47)

0.024

GSE24514

0.090 (1.96)

0.041 (40)

0.059 (50)

0.037 (40)

0.034 (30)

0.070

GSE4045

0.236 (1.47)

0.134 (24)

0.187 (37)

0.095 (47)

0.114 (29)

0.214

GSE14333

0.416 (9)

0.427 (9)

0.412 (1)

0.431 (1)

0.407

GSE27854

0.434 (5)

0.431 (25)

0.465 (13)

0.456 (8)

0.50

  1. The numbers in brackets represent the size, average size for ISIS method, of the gene set that corresponding to the minimum error rate. Boldface numbers indicate the lowest error rate (the highest accuracy) among the compared methods for the corresponding datasets.