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Error measures in quantitative structure-retention relationships studies
journal contribution
posted on 2023-05-19, 13:29 authored by Maryam TarajiMaryam Taraji, Paul HaddadPaul Haddad, Amos, RIJ, Mohammad TalebiMohammad Talebi, Szucs, R, Dolan, JW, Pohl, CAAn analysis and comparison of the use of four commonly used error measures (mean absolute error, percentage mean absolute error, root mean square error, and percentage root mean square error) for evaluating the predictive ability of quantitative structure-retention relationships (QSRR) models is reported. These error measures are used for reporting errors in the prediction of retention time of external test analytes, that is, analytes not employed during model development. The error-based validation metrics were compared using a simple descriptive statistic, the sum of squared residuals (SSR) of outliers to the edge of an error window. The comparisons demonstrate that Percentage Root Mean Squared Error of Prediction (RMSEP) provides the best estimate of the predictive ability of a QSRR model, having the lowest SSR value of 20.43.
Funding
Australian Research Council
Pfizer
Thermo Fisher Scientific Australia
History
Publication title
Journal of Chromatography AVolume
1524Pagination
298-302ISSN
0021-9673Department/School
School of Natural SciencesPublisher
Elsevier Science BvPlace of publication
Po Box 211, Amsterdam, Netherlands, 1000 AeRights statement
Copyright 2017 Crown Copyright. Published by Elsevier B.V.Repository Status
- Restricted