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Table 4 The minimum error rates yielded by Random Forest 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

0.003 (1)

0.030 (20)

0.118 (40)

0.015 (9)

0.0002 (40)

0.049

Breast

0.407 (4)

0.371 (50)

0.407 (48)

0.354 (48)

0.308 (45)

0.369

Srbct

0.092 (2.63)

0.069 (24)

0.074 (46)

0.009 (32)

0.003 (48)

0.0008

Prostate

0.097 (4.18)

0.200 (50)

0.140 (50)

0.069 (50)

0.062 (50)

0.088

All

0.0004 (1.018)

0.143 (40)

0.011 (50)

0 (40)

0 (20)

0

Lung

0.022 (3.26)

0.040 (30)

0.016 (48)

0.008 (46)

0.007 (48)

0.003

Carcinoma

0.171 (1.29)

0.003 (41)

0.017 (44)

0.019 (5)

0.026 (20)

0.027

GSE24514

0.107 (1.96)

0.054 (47)

0.063 (50)

0.036 (48)

0.032 (24)

0.041

GSE4045

0.27 (1.47)

0.134 (24)

0.187 (37)

0.137 (21)

0.114 (27)

0.205

GSE14333

0.423 (9)

0.421 (10)

0.438 (31)

0.437 (34)

0.414

GSE27854

0.448 (5)

0.401 (15)

0.444 (49)

0.451 (6)

0.488

  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.