{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T11:05:18Z","timestamp":1648983918096},"reference-count":9,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Neur. Syst."],"published-print":{"date-parts":[[2009,2]]},"abstract":"<jats:p> While no supervised learning algorithm can do well over all functions, we show that it may be possible to adapt a given function to a given supervised learning algorithm so as to allow the learning algorithm to better classify the original function. Although this seems counterintuitive, adapting the problem to the learner may result in an equivalent function that is \"easier\" for the algorithm to learn. One method of adapting a problem to the learner is to relabel the targets given in the training data. The following presents two problem adaptation methods, SOL-CTR-E and SOL-CTR-P, variants of Self-Oracle Learning with Confidence-based Target Relabeling (SOL-CTR) as a proof of concept for problem adaptation. The SOL-CTR methods produce \"easier\" target functions for training artificial neural networks (ANNs). Applying SOL-CTR over 41 data sets consistently results in a statistically significant (p &lt; 0.05) improvement in accuracy over 0\/1 targets on data sets containing over 10,000 training examples. <\/jats:p>","DOI":"10.1142\/s0129065709001793","type":"journal-article","created":{"date-parts":[[2009,2,26]],"date-time":"2009-02-26T09:11:54Z","timestamp":1235639514000},"page":"1-9","source":"Crossref","is-referenced-by-count":10,"title":["IMPROVING SUPERVISED LEARNING BY ADAPTING THE PROBLEM TO THE LEARNER"],"prefix":"10.1142","volume":"19","author":[{"given":"JOSHUA","family":"MENKE","sequence":"first","affiliation":[{"name":"Computer Science Department, Brigham Young University, 3365 TMCB, Provo, UT, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"TONY","family":"MARTINEZ","sequence":"additional","affiliation":[{"name":"Computer Science Department, Brigham Young University, 3365 TMCB, Provo, UT, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","unstructured":"P. L.\u00a0Bartlett, Advances in Neural Information Processing Systems\u00a09, eds. M. C.\u00a0Mozer, M. I.\u00a0Jordan and T.\u00a0Petsche (The MIT Press, 1997)\u00a0p. 134."},{"key":"rf5","unstructured":"R.\u00a0Caruana, S.\u00a0Baluja and T.\u00a0Mitchell, Advances in Neural Information Processing Systems, eds. D. S.\u00a0Touretzky, M. C.\u00a0Mozer and M. E.\u00a0Hasselmo (The MIT Press, Cambridge, MA, 1996)\u00a0pp. 959\u2013965."},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1162\/089976698300017197"},{"key":"rf9","unstructured":"A.\u00a0Krogh and J. A.\u00a0Hertz, Advances in Neural Information Processing Systems\u00a04, eds. J. E.\u00a0Moody, S. J.\u00a0Hanson and R. P.\u00a0Lippmann (Morgan Kaufmann Publishers, Inc., 1992)\u00a0pp. 950\u2013957."},{"key":"rf10","unstructured":"Y.\u00a0LeCun, Neural Networks: Tricks of the Trade, Lecture Notes in Computer Science\u00a01524, eds. G. B.\u00a0Orr and K.R.\u00a0M\u00fcller (Springer, 1996)\u00a0pp. 9\u201350."},{"key":"rf13","volume":"13","author":"Menke J. E.","journal-title":"Intelligent Data Analysis"},{"key":"rf14","doi-asserted-by":"publisher","DOI":"10.1109\/72.248452"},{"key":"rf16","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-006-6266-6"},{"key":"rf19","doi-asserted-by":"publisher","DOI":"10.1023\/A:1026530200837"}],"container-title":["International Journal of Neural Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129065709001793","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T02:05:16Z","timestamp":1565143516000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129065709001793"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,2]]},"references-count":9,"journal-issue":{"issue":"01","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2009,2]]}},"alternative-id":["10.1142\/S0129065709001793"],"URL":"https:\/\/doi.org\/10.1142\/s0129065709001793","relation":{},"ISSN":["0129-0657","1793-6462"],"issn-type":[{"value":"0129-0657","type":"print"},{"value":"1793-6462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,2]]}}}