Titlebook: Computational Science – ICCS 2020; 20th International C Valeria V. Krzhizhanovskaya,Gábor Závodszky,Jo?o T Conference proceedings 2020 Spri

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Jurijs Spiridonovs,Olga Bogdanovals for feature reconstruction. Variational Autoencoder with Arbitrary Conditioning (VAEAC) and Generative Adversarial Imputation Network (GAIN) were researched as representatives of generative models, while the denoising autoencoder (DAE) represented non-generative models. Performance of the models

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https://doi.org/10.1007/978-3-030-50423-6artificial intelligence; classification; classification methods; computer networks; data mining; data sec

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Computational Science – ICCS 2020978-3-030-50423-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/233088.jpg

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https://doi.org/10.1007/978-3-642-72048-2ammars, making it clear that using our answer set programs increases computational efficiency. The?research can be regarded as another evidence that solutions based on the?stable model (answer set) semantics of logic programming may be a?right choice for complex problems.

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Perspectives on Sustainable Growthwith three other approaches in the context of six performance measures. Comprehensive experimental results show that the proposed algorithm has better performance measures than the other ensemble methods for highly imbalanced datasets.