StAR: a simple tool for the statistical comparison of ROC curves

@article{Vergara2007StARAS,
  title={StAR: a simple tool for the statistical comparison of ROC curves},
  author={Ismael A. Vergara and Tom{\'a}s Norambuena and Evandro Ferrada and Alex W. Slater and Francisco J Melo},
  journal={BMC Bioinformatics},
  year={2007},
  volume={9},
  pages={265 - 265}
}
As in many different areas of science and technology, most important problems in bioinformatics rely on the proper development and assessment of binary classifiers. A generalized assessment of the performance of binary classifiers is typically carried out through the analysis of their receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) constitutes a popular indicator of the performance of a binary classifier. However, the assessment of the statistical significance… CONTINUE READING
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Clarke-Pearson DL: Comparing the Areas Under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach

  • ER Delong, DM Delong
  • Biometrics
  • 1988
Highly Influential
15 Excerpts

Berbaum KS: Montecarlo validation of the DorfmanBerbaum-Metz method using normalized pseudovalues and less data-based model simplification

  • SL Hillis
  • Academic radiology
  • 2005
3 Excerpts

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