{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T03:41:09Z","timestamp":1779248469799,"version":"3.51.4"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2010,1,27]],"date-time":"2010-01-27T00:00:00Z","timestamp":1264550400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"published-print":{"date-parts":[[2010,4]]},"DOI":"10.1007\/s10462-010-9156-z","type":"journal-article","created":{"date-parts":[[2010,1,26]],"date-time":"2010-01-26T06:14:22Z","timestamp":1264486462000},"page":"275-306","source":"Crossref","is-referenced-by-count":341,"title":["A study of the effect of different types of noise on the precision of supervised learning techniques"],"prefix":"10.1007","volume":"33","author":[{"given":"David F.","family":"Nettleton","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Albert","family":"Orriols-Puig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Albert","family":"Fornells","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2010,1,27]]},"reference":[{"key":"9156_CR1","first-page":"37","volume":"6","author":"DW Aha","year":"1991","unstructured":"Aha DW, Kibler D, Albert MK (1991) Instance-based learning algorithms. Mach Learn 6: 37\u201366","journal-title":"Mach Learn"},{"key":"9156_CR2","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/0020-7373(92)90018-G","volume":"36","author":"DW Aha","year":"1992","unstructured":"Aha DW (1992) Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms. Int J Man\u2013Mach Stud 36: 267\u2013287","journal-title":"Int J Man\u2013Mach Stud"},{"issue":"4","key":"9156_CR3","first-page":"343","volume":"2","author":"D Angluin","year":"1988","unstructured":"Angluin D, Laird P (1988) Learning from noisy examples. Mach Learn 2(4): 343\u2013370","journal-title":"Mach Learn"},{"key":"9156_CR4","unstructured":"Asuncion A, Newman DJ (2007) UCI repository of machine learning databases. Available by anonymous ftp to ics.uci.edu in the pub\/machine-learning-databases directory. University of California"},{"key":"9156_CR5","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1080\/01621459.1937.10503522","volume":"32","author":"M Friedman","year":"1937","unstructured":"Friedman M (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. J Am Stat Assoc 32: 675\u2013701","journal-title":"J Am Stat Assoc"},{"key":"9156_CR6","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1214\/aoms\/1177731944","volume":"11","author":"M Friedman","year":"1940","unstructured":"Friedman M (1940) A comparison of alternative tests of significance for the problem of m rankings. Ann Math Stat 11: 86\u201392","journal-title":"Ann Math Stat"},{"key":"9156_CR7","unstructured":"F\u00fcrnkranz J (1997) Noise-tolerant windowing. In: Proceedings of the 15th international joint conference on artificial intelligence (IJCAI-97), Nagoya, Japan. Morgan Kaufmann, pp 852\u2013857"},{"issue":"1","key":"9156_CR8","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1007\/BF01300374","volume":"14","author":"SA Goldman","year":"1995","unstructured":"Goldman SA, Sloan RH (1995) Can PAC learning algorithms tolerate random attribute noise. Algorithmica 14(1): 70\u201384 (Springer, New York)","journal-title":"Algorithmica"},{"key":"9156_CR9","doi-asserted-by":"crossref","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten, IH (2009) The WEKA data mining software: an update; SIGKDD Explor 10\u201318","DOI":"10.1145\/1656274.1656278"},{"key":"9156_CR10","volume-title":"Experiments in induction","author":"EB Hunt","year":"1966","unstructured":"Hunt EB, Martin J, Stone P (1966) Experiments in induction. Academic Press, New York"},{"key":"9156_CR11","unstructured":"John GH, Langley P (1995) Estimating continuous distributions in Bayesian classifiers. In: Eleventh conference on uncertainty in artificial intelligence, San Mateo, pp 338\u2013345"},{"issue":"6","key":"9156_CR12","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1145\/293347.293351","volume":"45","author":"M Kearns","year":"1998","unstructured":"Kearns M (1998) Efficient noise-tolerant learning from statistical queries. J ACM 45(6): 983\u20131006","journal-title":"J ACM"},{"key":"9156_CR13","doi-asserted-by":"crossref","first-page":"A33","DOI":"10.1088\/0967-3334\/17\/4A\/006","volume":"17","author":"S Meeson","year":"1996","unstructured":"Meeson S, Blott BH, Killingback ALT (1996) EIT data noise evaluation in the clinical environment. Physiol Meas 17: A33\u2013A38","journal-title":"Physiol Meas"},{"key":"9156_CR14","unstructured":"Nelson R (2005) Overcoming noise in data-acquisition systems (WEBCAST). Test Meas World. http:\/\/www.tmworld.com\/article\/319648- Overcomming_noise_in_data_acquisition_systems.php"},{"issue":"9","key":"9156_CR15","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1002\/int.1050","volume":"16","author":"D Nettleton","year":"2001","unstructured":"Nettleton D, Torra V (2001) A comparison of active set method and genetic algorithm approaches for learning weighting vectors in some aggregation operators. Int J Intel Syst 16(9): 1069\u20131083","journal-title":"Int J Intel Syst"},{"issue":"1\u20132","key":"9156_CR16","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S1386-5056(01)00173-3","volume":"63","author":"D Nettleton","year":"2001","unstructured":"Nettleton D, Mu\u00f1iz J (2001) Processing and representation of meta-data for sleep apnea diagnosis with an artificial intelligence approach. Int J Med Inform 63(1\u20132): 77\u201389","journal-title":"Int J Med Inform"},{"key":"9156_CR17","doi-asserted-by":"crossref","unstructured":"Platt J (1998) Fast training of support vector Machines using sequential minimal optimization. In: Sch\u00f6lkopf B, Burges CJC, Smola AJ (eds) Advances in kernel methods\u2014support vector learning, Chap 12. MIT Press, pp 169\u2013185","DOI":"10.7551\/mitpress\/1130.003.0016"},{"key":"9156_CR18","first-page":"81","volume":"1","author":"JR Quinlan","year":"1986","unstructured":"Quinlan JR (1986) Induction of decision trees. Mach Learn 1: 81\u2013106 (Kluwer Academic Publishers)","journal-title":"Mach Learn"},{"key":"9156_CR19","volume-title":"C4.5 programs for machine learning","author":"JR Quinlan","year":"1993","unstructured":"Quinlan JR (1993) C4.5 programs for machine learning. Morgan Kaufmann, San Mateo"},{"key":"9156_CR20","unstructured":"Sloan R (1988) Types of noise in data for concept learning. In: Annual workshop on computational learning theory. Proceedings of the first annual workshop on Computational learning theory: 91\u201396. SIGART: ACM special interest group on artificial intelligence"},{"issue":"3","key":"9156_CR21","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/0020-0190(95)00016-6","volume":"54","author":"RH Sloan","year":"1995","unstructured":"Sloan RH (1995) Four types of noise in data for PAC learning. Inform Process Lett 54(3): 157\u2013162","journal-title":"Inform Process Lett"},{"issue":"2","key":"9156_CR22","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1002\/(SICI)1098-111X(199702)12:2<153::AID-INT3>3.0.CO;2-P","volume":"12","author":"V Torra","year":"1997","unstructured":"Torra V (1997) The weighted owa operator. Int J Intell Syst 12(2): 153\u2013166","journal-title":"Int J Intell Syst"},{"key":"9156_CR23","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The nature of statistical learning theory","author":"VN Vapnik","year":"1995","unstructured":"Vapnik VN (1995) The nature of statistical learning theory. Springer Verlag, New York"},{"key":"9156_CR24","volume-title":"Data mining: practical machine learning tools and techniques","author":"IH Witten","year":"2005","unstructured":"Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco","edition":"2"},{"issue":"1","key":"9156_CR25","first-page":"1","volume":"14","author":"S Yu","year":"2007","unstructured":"Yu S, Zhou ZH, Steinbac M, Hand DJ, Steinberg D (2007) Top 10 algorithms in data mining. Knowl Inform Syst 14(1): 1\u201337","journal-title":"Knowl Inform Syst"},{"key":"9156_CR26","unstructured":"Zhu X, Wu X, Chen Q (2003) Eliminating class noise in large datasets. In: Proceedings of the 20th ICML international conference on machine learning, Washington, DC, pp 920\u2013927"},{"key":"9156_CR27","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s10462-004-0751-8","volume":"22","author":"X Zhu","year":"2004","unstructured":"Zhu X, Wu X (2004) Class noise vs. attribute noise: a quantitative study of their impacts. Artif Intel Rev 22: 177\u2013210 (Kluwer Academic Publishers)","journal-title":"Artif Intel Rev"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-010-9156-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10462-010-9156-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-010-9156-z","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T19:15:01Z","timestamp":1685387701000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10462-010-9156-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,1,27]]},"references-count":27,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2010,4]]}},"alternative-id":["9156"],"URL":"https:\/\/doi.org\/10.1007\/s10462-010-9156-z","relation":{},"ISSN":["0269-2821","1573-7462"],"issn-type":[{"value":"0269-2821","type":"print"},{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,1,27]]}}}