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Experiment databases: Creating a new platform for meta-learning research, , , и . Proceedings of the ICML/UAI/COLT Joint Planning to Learn Workshop (PlanLearn08), стр. 10-15. (2008)Classifier Chains: A Review and Perspectives., , , и . CoRR, (2019)Security and Data Accountability in Distributed Systems: A Provenance Survey., , и . HPCC/EUC, стр. 1571-1578. IEEE, (2013)Developing data mining applications.. KDD, стр. 225. ACM, (2012)Big Data with ADAMS., и . BigMine, том 41 из JMLR Workshop and Conference Proceedings, стр. 5-8. JMLR.org, (2015)Correction to: Adaptive random forests for evolving data stream classification., , , , , , , и . Mach. Learn., 108 (10): 1877-1878 (2019)Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract., , , , , , и . Meta-Knowledge Transfer @ ECML/PKDD, том 191 из Proceedings of Machine Learning Research, стр. 81-83. PMLR, (2022)MLR-Net: A multi-layer residual convolutional neural network for leather defect segmentation., , , и . Eng. Appl. Artif. Intell., (ноября 2023)Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them., , , , и . ECML/PKDD (1), том 8188 из Lecture Notes in Computer Science, стр. 465-479. Springer, (2013)Trainable guided attention based robust leather defect detection., , , , и . Eng. Appl. Artif. Intell., (2023)