See also Krstajic, D., Buturovic, L. J., Leahy, D. E., & Thomas, S. (2014). Cross-validation pitfalls when selecting and assessing regression and classification models. Journal of Cheminformatics, 6(1), 10. https://t.co/359He5eCXI
@daniela_witten @jmschreiber91 Nice thread, very much agreed with Our paper on how to avoid this and other CV pitfalls might be of interest: https://t.co/9M38HFlgkH
RT @ljbuturovic: @f2harrell @kareem_carr Some of the recent advances in cross-validation come from ML world: https://t.co/9M38HF3Ft9 http…
@f2harrell @kareem_carr Some of the recent advances in cross-validation come from ML world: https://t.co/9M38HF3Ft9 https://t.co/ToEGOmOvSH
RT @DrLukeOR: @weina_jin For a more detailed explanation, see the "Nested cross-validation for model assessment" section of: https://t.co/…
RT @DrLukeOR: @weina_jin For a more detailed explanation, see the "Nested cross-validation for model assessment" section of: https://t.co/…
RT @DrLukeOR: @weina_jin For a more detailed explanation, see the "Nested cross-validation for model assessment" section of: https://t.co/…
@DrLukeOR recommends our cross-validation paper: https://t.co/9M38HFlgkH
@weina_jin For a more detailed explanation, see the "Nested cross-validation for model assessment" section of: https://t.co/ZDYazT12p5 and here is the blog post from @weina_jin that reminded me to tweet about this topic https://t.co/p3WReFMSzc
@MaartenvSmeden @iiijohan This test for diagnosing cancer of unknown origin used univariable selection: https://t.co/Fbq4YaGdcQ The algorithm is described here: https://t.co/9ayr668Q3a
Background: developing an algorithm for accurately diagnosing CUP is difficult. Illustrations: a US Patent (https://t.co/jfF9UxPjDp) and this article (https://t.co/9M38HFlgkH) cover fraction of the ML methods we developed to diagnose CUP
“Repeated cross-validation We analysed the variation in the prediction performance that results from choosing a different split of the data.” https://t.co/NBffldv6re
RT @ljbuturovic: @fchollet Very true, but also very well known outside of DL community: https://t.co/mWTvsh0hhb
@fchollet Very true, but also very well known outside of DL community: https://t.co/mWTvsh0hhb
Great open access paper (2014) on the pitfalls of cross-validation: http://t.co/OV0EgmKZHz #datascience #analytics
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
MT @kdnuggets: Cross-validation pitfalls for regression and classification models - how to avoid them #DataMining http://t.co/iRF2Qvm0Ip
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
Cross-validation pitfalls for regression and classification models - and how to avoid them #DataScience http://t.co/2EJ6rTvJaa
#Crossvalidation pitfalls when selecting + assessing #regression + #classification models - J. of #Cheminformatics - http://t.co/DP5vDFwvre