{"year":"2019","has_accepted_license":"1","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - Subproject B2","_id":"10"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"status":"public","author":[{"id":"33176","last_name":"Wever","full_name":"Wever, Marcel Dominik","first_name":"Marcel Dominik","orcid":" https://orcid.org/0000-0001-9782-6818"},{"first_name":"Felix","full_name":"Mohr, Felix","last_name":"Mohr"},{"full_name":"Tornede, Alexander","last_name":"Tornede","id":"38209","first_name":"Alexander"},{"first_name":"Eyke","id":"48129","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke"}],"oa":"1","abstract":[{"lang":"eng","text":"Existing tools for automated machine learning, such as Auto-WEKA, TPOT, auto-sklearn, and more recently ML-Plan, have shown impressive results for the tasks of single-label classification and regression. Yet, there is only little work on other types of machine learning problems so far. In particular, there is almost no work on automating the engineering of machine learning solutions for multi-label classification (MLC). We show how the scope of ML-Plan, an AutoML-tool for multi-class classification, can be extended towards MLC using MEKA, which is a multi-label extension of the well-known Java library WEKA. The resulting approach recursively refines MEKA's multi-label classifiers, nesting other multi-label classifiers for meta algorithms and single-label classifiers provided by WEKA as base learners. In our evaluation, we find that the proposed approach yields strong results and performs significantly better than a set of baselines we compare with."}],"file_date_updated":"2019-09-10T08:20:44Z","department":[{"_id":"355"}],"_id":"10232","title":"Automating Multi-Label Classification Extending ML-Plan","date_created":"2019-06-11T21:33:06Z","citation":{"ieee":"M. D. Wever, F. Mohr, A. Tornede, and E. Hüllermeier, “Automating Multi-Label Classification Extending ML-Plan,” presented at the 6th ICML Workshop on Automated Machine Learning (AutoML 2019), Long Beach, CA, USA, 2019.","mla":"Wever, Marcel Dominik, et al. <i>Automating Multi-Label Classification Extending ML-Plan</i>. 2019.","ama":"Wever MD, Mohr F, Tornede A, Hüllermeier E. Automating Multi-Label Classification Extending ML-Plan. In: ; 2019.","apa":"Wever, M. D., Mohr, F., Tornede, A., &#38; Hüllermeier, E. (2019). Automating Multi-Label Classification Extending ML-Plan. Presented at the 6th ICML Workshop on Automated Machine Learning (AutoML 2019), Long Beach, CA, USA.","bibtex":"@inproceedings{Wever_Mohr_Tornede_Hüllermeier_2019, title={Automating Multi-Label Classification Extending ML-Plan}, author={Wever, Marcel Dominik and Mohr, Felix and Tornede, Alexander and Hüllermeier, Eyke}, year={2019} }","short":"M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.","chicago":"Wever, Marcel Dominik, Felix Mohr, Alexander Tornede, and Eyke Hüllermeier. “Automating Multi-Label Classification Extending ML-Plan,” 2019."},"user_id":"33176","ddc":["006"],"language":[{"iso":"eng"}],"conference":{"name":"6th ICML Workshop on Automated Machine Learning (AutoML 2019)","end_date":"2019-06-15","start_date":"2019-06-09","location":"Long Beach, CA, USA"},"date_updated":"2022-01-06T06:50:33Z","type":"conference","file":[{"file_id":"13177","file_name":"Automating_MultiLabel_Classification_Extending_ML-Plan.pdf","access_level":"open_access","content_type":"application/pdf","relation":"main_file","date_created":"2019-09-10T08:19:01Z","date_updated":"2019-09-10T08:20:44Z","file_size":388191,"creator":"wever"}]}