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| Căutarea după subiecte similare conform CZU |
| 004.93'11 (1) |
| Informatică aplicată. Tehnici bazate pe calculator cu aplicații practice (440) |
 SM ISO690:2012POPUKAYLO, Vladimir, SHMELYOVA, Anastasiya. Application of the Multidimensional Point Distribution Method in Machine Learning Tasks with Imbalanced Data. In: Workshop on Intelligent Information Systems, Ed. 2023, 19-21 octombrie 2023, Chişinău. Chişinau, Moldova: Valnex, 2023, pp. 191-198. ISBN 978-9975-68-492-7.. |
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| Workshop on Intelligent Information Systems 2023 | ||||||
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Conferința "Workshop on Intelligent Information Systems" 2023, Chişinău, Moldova, 19-21 octombrie 2023 | ||||||
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| CZU: 004.93'11 | ||||||
| Pag. 191-198 | ||||||
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The article addresses the problem of using imbalanced data in multi-class classification tasks. It briefly examines the main existing approaches and proposes the application of the multidimensional point distribution method to balance classes. The algorithm for applying this method is described, and an experiment is conducted using synthetic data. The results are compared with existing algorithms such as random oversampling of the small class, ADASYN, SMOTE, ASMO, and SVMSMOTE. The article shows the possibility of using the multidimensional point distribution method in principle to improve the quality of machine learning algorithms in conditions of imbalanced data. |
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| Cuvinte-cheie machine learning, classification task, tabular data processing, imbalanced data, multidimensional point distribution method |
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