BenchMetrics: a systematic benchmarking method for binary classification performance metrics-Reference-Cited by-同舟云学术

BenchMetrics: a systematic benchmarking method for binary classification performance metrics

Published:2021-08-22 Issue:21 Volume:33 Page:14623-14650
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Canbek Gürol^ORCID,Taskaya Temizel Tugba^ORCID,Sagiroglu Seref^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-06103-6.pdf

Reference40 articles.

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2. Staartjes VE, Schröder ML (2018) Letter to the Editor. Class imbalance in machine learning for neurosurgical outcome prediction: are our models valid? J Neurosurg Spine 29:611–612. https://doi.org/10.3171/2018.5.SPINE18543

3. Brown JB (2018) Classifiers and their metrics quantified. Mol Inform 37:1–11. https://doi.org/10.1002/minf.201700127

4. Sokolova M (2006) Assessing invariance properties of evaluation measures. Proc Work Test Deployable Learn Decis Syst 19th Neural Inf Process Syst Conf (NIPS 2006) 1–6

5. Ranawana R, Palade V (2006) Optimized precision—a new measure for classifier performance evaluation. In: 2006 IEEE International Conference on Evolutionary Computation. IEEE, Vancouver, BC, Canada, pp 2254–2261

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