{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T12:13:01Z","timestamp":1763640781806,"version":"3.28.0"},"reference-count":10,"publisher":"IEEE Comput. Soc","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1109\/tai.2002.1180809","type":"proceedings-article","created":{"date-parts":[[2003,6,26]],"date-time":"2003-06-26T11:35:00Z","timestamp":1056627300000},"page":"233-238","source":"Crossref","is-referenced-by-count":4,"title":["Error-based pruning of decision trees grown on very large data sets can work!"],"prefix":"10.1109","author":[{"given":"L.O.","family":"Hall","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Collins","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K.W.","family":"Bowyer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Banfield","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref4","first-page":"254","article-title":"The effects of training set size on decision tree complexity","author":"oates","year":"1997","journal-title":"Proceedings of the Fourteenth International Conference on Machine Learning"},{"key":"ref3","first-page":"294","article-title":"Large datasets lead to overly complex models: an explanation and a solution","author":"oates","year":"1998","journal-title":"Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1023\/A:1022604100933"},{"journal-title":"UCI Machine Learning Data Repository","year":"0","key":"ref6"},{"article-title":"C4.5: Programs for Machine Learning","year":"1993","author":"quinlan","key":"ref5"},{"key":"ref8","first-page":"163","article-title":"An Analysis of Reduced Error Pruning Journal of Artifcial Intelligence Research","volume":"15","author":"elomaa","year":"2001"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1999.3091"},{"key":"ref2","article-title":"Toward a theoretical understanding of why and when decision tree pruning algorithms fail","author":"oates","year":"1999","journal-title":"AAAI-99"},{"article-title":"Is Default Pruning Enough? A Study in C4.5 Error-Based Pruning","year":"2002","author":"collins","key":"ref9"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/34.589207"}],"event":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2002)","acronym":"TAI-02","location":"Washington, DC, USA"},"container-title":["14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings."],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx5\/8408\/26514\/01180809.pdf?arnumber=1180809","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,3,13]],"date-time":"2017-03-13T18:57:13Z","timestamp":1489431433000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/1180809\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"references-count":10,"URL":"https:\/\/doi.org\/10.1109\/tai.2002.1180809","relation":{},"subject":[]}}