Titlebook: Computational Science – ICCS 2021; 21st International C Maciej Paszynski,Dieter Kranzlmüller,Peter M.A. Sl Conference proceedings 2021 Spri

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Predictability Classes for Forecasting Clients Behavior by Transactional Dataclient’s next purchase or the next location visited that focus on achieving the best possible prediction quality in terms of different quality metrics. Within such approaches, the quality is however usually evaluated on the entire set of clients, without dividing them into classes with a different p

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A Non-intrusive Machine Learning Solution for Malware Detection and Data Theft Classification in Smaattackers. Successful mobile malware attacks could steal a user’s location, photos, or even banking information. Due to the lack of post-attack strategies, firms also risk going out of business due to data theft. Thus, there is a need to not only detect malware intrusion in smartphones but to also i

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Exact Searching for the Smallest Deterministic Automaton a required size. We provide an implementation of this approach, which we use to conduct experiments on a series of benchmarks. The results showed that our method outperforms in terms of CPU time other SAT and SMT approaches and other exact algorithms on prepared benchmarks.

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Inexorable

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Sustainable Ecological Engineering Designe last step. We prove that, under some regularity conditions, our procedure satisfies the screening property. We also conduct some simulation study in order to compare the proposed classification procedure with the oracle method. Prediction accuracy of the proposed method has been verified for some selected real datasets.

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https://doi.org/10.1007/978-981-99-1191-2re proposed in this paper is using the multi-objective genetic algorithm ., for a search of the optimal subset of the learning set. The paper presents a detailed description of the considered method. Moreover, the proposed algorithm has been compared with a selection of reference algorithms showing promising results.

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