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

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Analysis of Semestral Progress in Higher Technical Education with HMM Modelserging from student’s results. We also try to predict the final students’ results on the basis of their partial grades. A new, classification approach for this problem, using properties of HMMs is proposed: High and Low State Model (HLSM).
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Orsolya Diófási-Kovács,László Valkórithm was compared with our earlier proposal and state-of-the-art algorithms using highly imbalanced datasets. The performed experiments show that the proposed modification is statistically better for a larger number of reference classifiers than the original algorithm.
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https://doi.org/10.1007/978-981-99-1191-2ther incomplete vectors, unlike in conventional methods, where only complete vectors could be used in the imputation process. The paper also describes a test protocol, where the Cross Validation with a Set Substitution method is used as an evaluation tool for scoring missing value imputation methods.
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Soft Confusion Matrix Classifier for Stream Classificationft. This is done by employing the ADWIN-driven concept drift detector that is not only used to detect the drift but also to control the size of the neighbourhood. The obtained experimental results show that the proposed approach significantly outperforms the reference methods.
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