{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-nips17-competition-a-multi-view-ensemble","title":"A Multi-View Ensemble Classification Model for Clinically Actionable Genetic Mutations","arxiv_id":"1806.09737","date":"2018-06-26","proceeding":null,"authors":["Xi Sheryl Zhang","Dandi Chen","Yongjun Zhu","Chao Che","Chang Su","Sendong Zhao","Xu Min","Fei Wang"],"abstract":"This paper presents details of our winning solutions to the task IV of NIPS\n2017 Competition Track entitled Classifying Clinically Actionable Genetic\nMutations. The machine learning task aims to classify genetic mutations based\non text evidence from clinical literature with promising performance. We\ndevelop a novel multi-view machine learning framework with ensemble\nclassification models to solve the problem. During the Challenge, feature\ncombinations derived from three views including document view, entity text\nview, and entity name view, which complements each other, are comprehensively\nexplored. As the final solution, we submitted an ensemble of nine basic\ngradient boosting models which shows the best performance in the evaluation.\nThe approach scores 0.5506 and 0.6694 in terms of logarithmic loss on a fixed\nsplit in stage-1 testing phase and 5-fold cross validation respectively, which\nalso makes us ranked as a top-1 team out of more than 1,300 solutions in NIPS\n2017 Competition Track IV.","url_abs":"http://arxiv.org/abs/1806.09737v2","url_pdf":"http://arxiv.org/pdf/1806.09737v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-nips17-competition-a-multi-view-ensemble","repo_url":"https://github.com/sheryl-ai/NeurIPS17","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"the-nips17-competition-a-multi-view-ensemble","repo_url":"https://github.com/sheryl-ai/NeurIPS17-Competition-Classifying-Genetic-Mutations","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}