Multi-Level Comparison of Machine Learning Classifiers and Their Performance Metrics

Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry
Anita RáczK Héberger

Abstract

Machine learning classification algorithms are widely used for the prediction and classification of the different properties of molecules such as toxicity or biological activity. the prediction of toxic vs. non-toxic molecules is important due to testing on living animals, which has ethical and cost drawbacks as well. The quality of classification models can be determined with several performance parameters. which often give conflicting results. In this study, we performed a multi-level comparison with the use of different performance metrics and machine learning classification methods. Well-established and standardized protocols for the machine learning tasks were used in each case. The comparison was applied to three datasets (acute and aquatic toxicities) and the robust, yet sensitive, sum of ranking differences (SRD) and analysis of variance (ANOVA) were applied for evaluation. The effect of dataset composition (balanced vs. imbalanced) and 2-class vs. multiclass classification scenarios was also studied. Most of the performance metrics are sensitive to dataset composition, especially in 2-class classification problems. The optimal machine learning algorithm also depends significantly on the composition of the dataset.

References

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Apr 5, 2019·Molecular Informatics·Anita RáczKároly Héberger
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Citations

Aug 31, 2020·Psychotherapy Research : Journal of the Society for Psychotherapy Research·Katie Aafjes-van DoornMarc Aafjes
Mar 30, 2020·Journal of Computer-aided Molecular Design·Anita Rácz, György M Keserű
Aug 1, 2020·Frontiers in Molecular Biosciences·Gennady M VerkhivkerPeng Tao
Mar 7, 2021·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Anita RáczKároly Héberger
Apr 17, 2021·Journal of Clinical Monitoring and Computing·Beatriz Nistal-Nuño
May 20, 2021·Applied Clinical Informatics·Xinran LiuAtul J Butte
May 17, 2021·Food Research International·Attila GereSándor Kovács
Jul 16, 2021·Skeletal Radiology·Florian A Huber, Roman Guggenberger

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Software Mentioned

Decorate
WEKA
COVAT
VBA
KNIME Analytics Platform
SRD

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