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Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme., , , , и . AIAI, том 559 из IFIP Advances in Information and Communication Technology, стр. 37-49. Springer, (2019)Rotation forest of random subspace models., , , , и . Intell. Decis. Technol., 16 (2): 315-324 (2022)Random Resampling in the One-Versus-All Strategy for Handling Multi-class Problems., , , и . EANN, том 744 из Communications in Computer and Information Science, стр. 111-121. Springer, (2017)A Deep Dense Neural Network for Bankruptcy Prediction., , , и . EANN, том 1000 из Communications in Computer and Information Science, стр. 435-444. Springer, (2019)Combining random forest and support vector machines for semi-supervised learning., и . Panhellenic Conference on Informatics, стр. 123-128. ACM, (2015)Combining Active Learning with Self-train algorithm for classification of multimodal problems., , , , и . IISA, стр. 1-8. IEEE, (2019)Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme., , , , и . Entropy, 21 (10): 988 (2019)Stacking Strong Ensembles of Classifiers., , , и . AIAI, том 559 из IFIP Advances in Information and Communication Technology, стр. 545-556. Springer, (2019)Increasing Diversity in Random Forests Using Naive Bayes., , и . AIAI, том 475 из IFIP Advances in Information and Communication Technology, стр. 75-86. Springer, (2016)Combining Prototype Selection with Local Boosting., , и . AIAI, том 475 из IFIP Advances in Information and Communication Technology, стр. 94-105. Springer, (2016)