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Table 5 The average ROC score for four algorithms and four functional groups

From: Predicting gene function using few positive examples and unlabeled ones

algorithms

< 60

60-100

100-300

> 300

twoclass

0.5081

0.7448

0.7743

0.7044

twoclassbal

0.5207

0.7529

0.8002

0.7118

PSoL

0.5313

0.7626

0.7726

0.7142

SPE-RNE

0.6827

0.7969

0.8084

0.7266

  1. ROC score, that is area under ROC curve, is a widely-accepted performance measure for prediction classification problem. The larger ROC score is, the better the performance of classification algorithm is.
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BMC Genomics

ISSN: 1471-2164

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