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Table 3 Confusion Matrices.

From: Biomarker Discovery and Redundancy Reduction towards Classification using a Multi-factorial MALDI-TOF MS T2DM Mouse Model Dataset

    

CHF

 

HF

 

SD

    

nFeat

 

Method

 

CHF

HF

SD

 

CHF

HF

SD

 

CHF

HF

SD

 

Error

 

P-Value

3

 

ANOVA

 

33

14

18

 

17

24

24

 

16

16

36

 

0.53

 

0.0028

  

ACO

 

45

4

16

 

10

33

22

 

11

16

41

 

0.4

 

1e-08

  

Cluster ANOVA

 

40

12

13

 

15

28

22

 

9

16

43

 

0.44

 

1e-06

5

 

ANOVA

 

36

13

16

 

18

22

25

 

20

11

37

 

0.52

 

0.006

  

ACO

 

48

3

14

 

12

33

20

 

10

15

43

 

0.37

 

2.7e-08

  

Cluster ANOVA

 

40

13

12

 

15

38

12

 

4

24

40

 

0.4

 

6.7e-07

8

 

ANOVA

 

41

12

12

 

16

34

15

 

6

22

40

 

0.42

 

9e-06

  

ACO

 

45

5

15

 

12

30

23

 

4

18

46

 

0.39

 

5.5e-07

  

Cluster ANOVA

 

43

10

12

 

14

35

16

 

5

19

44

 

0.38

 

3.3e-07

  1. Confusion matrix for 10-fold cross validation for experimental factor diet using random forest classifier. The feature selection was done by three different methods: ANOVA, ant colony optimization (ACO) and cluster-based ANOVA. The feature selection was performed three times with different number of features: 3, 5 and 8. Numbers in bold print represents true positives.
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BMC Bioinformatics

ISSN: 1471-2105

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