Count on kappa.

Bibliographic Details
Title: Count on kappa.
Authors: Czodrowski, Paul1 paul.czodrowski@merckgroup.com
Source: Journal of Computer-Aided Molecular Design. Nov2014, Vol. 28 Issue 11, p1049-1055. 7p.
Subject Terms: *COHEN'S kappa coefficient (Statistics), *CHEMINFORMATICS, *MACHINE learning, *CLASSIFICATION, *ESTIMATION theory, *EVALUATION of medical care
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. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computer-Aided Molecular Design is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: *<searchLink fieldCode="DE" term="%22COHEN'S+kappa+coefficient+%28Statistics%29%22">COHEN'S kappa coefficient (Statistics)</searchLink><br />*<searchLink fieldCode="DE" term="%22CHEMINFORMATICS%22">CHEMINFORMATICS</searchLink><br />*<searchLink fieldCode="DE" term="%22MACHINE+learning%22">MACHINE learning</searchLink><br />*<searchLink fieldCode="DE" term="%22CLASSIFICATION%22">CLASSIFICATION</searchLink><br />*<searchLink fieldCode="DE" term="%22ESTIMATION+theory%22">ESTIMATION theory</searchLink><br />*<searchLink fieldCode="DE" term="%22EVALUATION+of+medical+care%22">EVALUATION of medical care</searchLink>
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  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Computer-Aided Molecular Design is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Nov2014
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