{"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/opposite-neighborhood-a-new-method-to-select","title":"Opposite neighborhood: a new method to select reference points of minimal learning machines","arxiv_id":null,"date":"2018-03-22","proceeding":"26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2018 3","authors":["Madson Luiz Dantas Dias","Lucas Silva De Sousa","Ajalmar Rêgo da Rocha Neto","Amauri H. de Souza Júnior"],"abstract":"This paper introduces a new approach to select reference points in minimal learning machines (MLMs) for classification tasks. The MLM training procedure comprises the selection of a subset of the data, named reference points (RPs), that is used to build a linear regression model between distances taken in the input and output spaces. In this matter, we propose a strategy, named opposite neighborhood (ON), to tackle the problem of selecting RPs by locating RPs out of class-overlapping regions. Experiments were carried out using UCI data sets. As a result, the proposal is able to both produce sparser models and achieve competitive performance when compared to the regular MLM.","url_abs":"https://link.springer.com/chapter/10.1007%2F978-3-319-95312-0_34","url_pdf":"https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2018-198.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":"opposite-neighborhood-a-new-method-to-select","repo_url":"https://github.com/omadson/scikit-mlm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"linear-regression","method_name":"Linear Regression"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}