{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T13:14:02Z","timestamp":1666012442940},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,17]]},"abstract":"<jats:p>Classification systems based Machine Learning hide the logic of their internal decision processes from the users. Hence, post-hoc explanations about their predictions are often required. This paper proposes Fuzzy-LORE, a method that generates local explanations for fuzzy-based Machine Learning systems. First, it learns a local fuzzy decision tree using a set of synthetic neighbours from the input instance. Then, it extracts from the logic of the fuzzy decision tree a meaningful explanation consisting of a set of decision rules (which explain the reasons behind the decision), a set of counterfactual rules (which inform of small changes in the instance\u2019s features that would lead to a different outcome), and finally a set of specific counterfactual examples. Our experiments on a real-world medical dataset show that Fuzzy-LORE outperforms prior approaches and methods for generating local explanations.<\/jats:p>","DOI":"10.3233\/faia220357","type":"book-chapter","created":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T12:38:19Z","timestamp":1666010299000},"source":"Crossref","is-referenced-by-count":0,"title":["Fuzzy-LORE: A Method for Extracting Local and Counterfactual Explanations Using Fuzzy Decision Trees"],"prefix":"10.3233","author":[{"given":"Najlaa","family":"Maaroof","sequence":"first","affiliation":[{"name":"ITAKA-Intelligent Technologies for Advanced Knowledge Acquisition \u2013 Departament d\u2019Enginyeria Inform\u00e0tica i Matem\u00e0tiques, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain"}]},{"given":"Antonio","family":"Moreno","sequence":"additional","affiliation":[{"name":"ITAKA-Intelligent Technologies for Advanced Knowledge Acquisition \u2013 Departament d\u2019Enginyeria Inform\u00e0tica i Matem\u00e0tiques, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain"}]},{"given":"Mohammed","family":"Jabreel","sequence":"additional","affiliation":[{"name":"ITAKA-Intelligent Technologies for Advanced Knowledge Acquisition \u2013 Departament d\u2019Enginyeria Inform\u00e0tica i Matem\u00e0tiques, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain"}]},{"given":"Aida","family":"Valls","sequence":"additional","affiliation":[{"name":"ITAKA-Intelligent Technologies for Advanced Knowledge Acquisition \u2013 Departament d\u2019Enginyeria Inform\u00e0tica i Matem\u00e0tiques, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Artificial Intelligence Research and Development"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220357","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T12:38:25Z","timestamp":1666010305000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220357"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,17]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220357","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,17]]}}}