{"type":"ScholarlyArticle","title":"Rule Induction and Instance-Based Learning: A Unified Approach","authors":[{"name":"Pedro M. Domingos","slug":"pedro-m-domingos","given":"Pedro M.","family":"Domingos","affiliation":""}],"abstract":"This paper presents a new approach to inductive learning that combines aspects of instancebased learning and rule induction in a single simple algorithm. The RISE system searches for rules in a specific-to-general fashion, starting with one rule per training example, and avoids some of the difficulties of separate-andconquer approaches by evaluating each proposed induction step globally, i.e., through an efficient procedure that is equivalent to checking the accuracy of the rule set as a whole on every training example. Classification is performed using a best-match strategy, and reduces to nearest-neighbor if all generalizations of instances were rejected. An extensive empirical study shows that RISE consistently achieves higher accuracies than state-of-the-art representatives of its \"parent\" paradigms {PEBLS and CN2), and also outperforms a decision-tree learner {C4.5) in 13 out of 15 test domains {in 10 with 95% confidence).","doi":null,"url":"https://ijcai.org/proceedings/1995/158","pdf":"https://ijcai.org/proceedings/1995/0158.pdf","markdown":"https://ijcai.org/proceedings/1995/158.md","bibtex":"https://ijcai.org/proceedings/1995/bibtex/158","volume":{"slug":"1995","title":"Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1995","url":"https://ijcai.org/proceedings/1995/","year":1995,"location":"Montréal, Québec, Canada","dates":"","editors":"Chris S. Mellish","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Learning","track":"Learning","number":158,"pages":{"first":1226,"last":1231},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}