Abstract:
:In the 1960s, the kappa statistic was introduced for the estimation of chance agreement in inter- and intra-rater reliability studies. The kappa statistic was strongly pushed by the medical field where it could be successfully applied via analyzing diagnoses of identical patient groups. Kappa is well suited for classification tasks where ranking is not considered. The main advantage of kappa is its simplicity and the general applicability to multi-class problems which is the major difference to receiver operating characteristic area under the curve. In this manuscript, I will outline the usage of kappa for classification tasks, and I will evaluate the role and uses of kappa in specifically machine learning and cheminformatics.
journal_name
J Comput Aided Mol Desjournal_title
Journal of computer-aided molecular designauthors
Czodrowski Pdoi
10.1007/s10822-014-9759-6subject
Has Abstractpub_date
2014-11-01 00:00:00pages
1049-55issue
11eissn
0920-654Xissn
1573-4951journal_volume
28pub_type
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journal_title:Journal of computer-aided molecular design
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journal_title:Journal of computer-aided molecular design
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journal_title:Journal of computer-aided molecular design
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journal_title:Journal of computer-aided molecular design
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journal_title:Journal of computer-aided molecular design
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journal_title:Journal of computer-aided molecular design
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journal_title:Journal of computer-aided molecular design
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journal_title:Journal of computer-aided molecular design
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