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Big Data with ADAMS.

, and . BigMine, volume 41 of JMLR Workshop and Conference Proceedings, page 5-8. JMLR.org, (2015)

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