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Table 1 Cost matrix for a 2-class (class 0 and class 1) classifier

From: MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm

 

Predited class

 

0

1

Given class

0

CTN=0

CFP=10

 

1

CFN=1

CTP=0

  1. In this case, the cost of a false positive is 10 times higher than the cost of a false negative. CTN = cost of a true negative, CFP = cost of a false positive, CFN = cost of a false negative, and CTP = cost of a true positive
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BMC Bioinformatics

ISSN: 1471-2105

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