Corpus ID: 211252397

cutpointr: Improved Estimation and Validation of Optimal Cutpoints in R

@article{Thiele2020cutpointrIE,
  title={cutpointr: Improved Estimation and Validation of Optimal Cutpoints in R},
  author={Christian Thiele and G. Hirschfeld},
  journal={arXiv: Computation},
  year={2020}
}

• Christian Thiele, G. Hirschfeld
• Published 2020
• Computer Science, Mathematics
• arXiv: Computation

'Optimal cutpoints' for binary classification tasks are often established by testing which cutpoint yields the best discrimination, for example the Youden index, in a specific sample. This results in 'optimal' cutpoints that are highly variable and systematically overestimate the out-of-sample performance. To address these concerns, the cutpointr package offers robust methods for estimating optimal cutpoints and the out-of-sample performance. The robust methods include bootstrapping and… Expand

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