{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T18:51:19Z","timestamp":1780512679900,"version":"3.54.1"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2018,8,30]],"date-time":"2018-08-30T00:00:00Z","timestamp":1535587200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100004396","name":"Thailand Research Fund","doi-asserted-by":"publisher","award":["MRG59080235"],"award-info":[{"award-number":["MRG59080235"]}],"id":[{"id":"10.13039\/501100004396","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Pattern Anal Applic"],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1007\/s10044-018-0750-z","type":"journal-article","created":{"date-parts":[[2018,8,30]],"date-time":"2018-08-30T12:23:51Z","timestamp":1535631831000},"page":"95-111","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Towards instance-dependent label noise-tolerant classification: a probabilistic approach"],"prefix":"10.1007","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9158-1570","authenticated-orcid":false,"given":"Jakramate","family":"Bootkrajang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeerayut","family":"Chaijaruwanich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,8,30]]},"reference":[{"key":"750_CR1","doi-asserted-by":"crossref","unstructured":"Beigman E, Klebanov BB (2009) Learning with annotation noise. In: ACL 2009, Proceedings of the 47th annual meeting of the association for computational linguistics, 2\u20137 August 2009, Singapore, pp 280\u2013287","DOI":"10.3115\/1687878.1687919"},{"key":"750_CR2","doi-asserted-by":"crossref","unstructured":"Kolcz A, Cormack GV (2009) Genre-based decomposition of email class noise. In: SIGKDD\u201909, pp 427\u2013436","DOI":"10.1145\/1557019.1557070"},{"key":"750_CR3","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.apgeog.2015.12.006","volume":"67","author":"BA Johnson","year":"2016","unstructured":"Johnson BA, Iizuka K (2016) Integrating openstreetmap crowdsourced data and landsat time-series imagery for rapid land use\/land cover (LULC) mapping: case study of the laguna de bay area of the philippines. Appl Geogr 67:140\u2013149","journal-title":"Appl Geogr"},{"key":"750_CR4","doi-asserted-by":"crossref","unstructured":"Snow R, O\u2019Connor B, Jurafsky D, Ng AY (2008) Cheap and fast\u2014but is it good? Evaluating non-expert annotations for natural language tasks. In: EMNLP, pp 254\u2013263","DOI":"10.3115\/1613715.1613751"},{"key":"750_CR5","doi-asserted-by":"crossref","unstructured":"Shen D, Ruvini J-D, Sarwar B (2012) Large-scale item categorization for e-commerce. In: Proceedings of the 21st ACM international conference on information and knowledge management, CIKM \u201912, New York, NY, USA. ACM, pp 595\u2013604","DOI":"10.1145\/2396761.2396838"},{"key":"750_CR6","unstructured":"Xiao T, Xia T, Yang Y, Huang C, Wang X (2015) Learning from massive noisy labeled data for image classification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2691\u20132699"},{"issue":"5","key":"750_CR7","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1109\/TNNLS.2013.2292894","volume":"25","author":"B Fr\u00e9nay","year":"2014","unstructured":"Fr\u00e9nay B, Verleysen M (2014) Classification in the presence of label noise: a survey. IEEE Trans Neural Netw Learn Syst 25(5):845\u2013869","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"750_CR8","unstructured":"Menon AK, van Rooyen B, Natarajan N (2016) Learning from binary labels with instance-dependent corruption. arXiv preprint arXiv:1605.00751"},{"key":"750_CR9","unstructured":"Biggio B, Nelson B, Laskov P (2011) Support vector machines under adversarial label noise. In: ACML, volume\u00a020 of JMLR proceedings, pp 97\u2013112. JMLR.org"},{"issue":"388","key":"750_CR10","doi-asserted-by":"publisher","first-page":"899","DOI":"10.1080\/01621459.1984.10477109","volume":"79","author":"RS Chhikara","year":"1984","unstructured":"Chhikara RS, McKeon J (1984) Linear discriminant analysis with misallocation in training samples. J Am Stat Assoc 79(388):899\u2013906","journal-title":"J Am Stat Assoc"},{"key":"750_CR11","unstructured":"Lawrence ND, Sch\u00f6lkopf B (2001) Estimating a Kernel fisher discriminant in the presence of label noise. In: ICML\u201901. Morgan Kaufmann, pp 306\u2013313"},{"issue":"12","key":"750_CR12","doi-asserted-by":"publisher","first-page":"3349","DOI":"10.1016\/j.patcog.2007.05.006","volume":"40","author":"Y Li","year":"2007","unstructured":"Li Y, Wessels LFA, de Ridder D, Reinders MJT (2007) Classification in the presence of class noise using a probabilistic kernel Fisher method. Pattern Recognit 40(12):3349\u20133357","journal-title":"Pattern Recognit"},{"key":"750_CR13","first-page":"1297","volume":"11","author":"VC Raykar","year":"2010","unstructured":"Raykar VC, Shipeng Y, Zhao LH, Valadez GH, Florin C, Bogoni L, Moy L (2010) Learning from crowds. J Mach Learn Res 11:1297\u20131322","journal-title":"J Mach Learn Res"},{"key":"750_CR14","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/978-3-642-33460-3_15","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Jakramate Bootkrajang","year":"2012","unstructured":"Bootkrajang J, Kab\u00e1n A (2012) Label-noise robust logistic regression and its applications. In: ECML-PKDD\u201912, pp 143\u2013158"},{"issue":"11","key":"750_CR15","doi-asserted-by":"publisher","first-page":"3641","DOI":"10.1016\/j.patcog.2014.05.007","volume":"47","author":"J Bootkrajang","year":"2014","unstructured":"Bootkrajang J, Kab\u00e1n A (2014) Learning kernel logistic regression in the presence of class label noise. Pattern Recognit 47(11):3641\u20133655","journal-title":"Pattern Recognit"},{"key":"750_CR16","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/0031-3203(92)90008-7","volume":"25","author":"G Lugosi","year":"1992","unstructured":"Lugosi G (1992) Learning with an unreliable teacher. Pattern Recognit 25:79\u201387","journal-title":"Pattern Recognit"},{"issue":"3","key":"750_CR17","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1007\/s10994-009-5165-z","volume":"78","author":"PM Long","year":"2010","unstructured":"Long PM, Servedio RA (2010) Random classification noise defeats all convex potential boosters. Mach Learn 78(3):287\u2013304","journal-title":"Mach Learn"},{"key":"750_CR18","unstructured":"Natarajan N, Dhillon IS, Ravikumar PK, Tewari A (2013) Learning with noisy labels. In: NIPS\u201913, pp 1196\u20131204"},{"issue":"3","key":"750_CR19","doi-asserted-by":"publisher","first-page":"1146","DOI":"10.1109\/TSMCB.2012.2223460","volume":"43","author":"N Manwani","year":"2013","unstructured":"Manwani N, Sastry PS (2013) Noise tolerance under risk minimization. IEEE Trans Cybernet 43(3):1146\u20131151","journal-title":"IEEE Trans Cybernet"},{"key":"750_CR20","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.neucom.2014.09.081","volume":"160","author":"A Ghosh","year":"2015","unstructured":"Ghosh A, Manwani N, Sastry PS (2015) Making risk minimization tolerant to label noise. Neurocomputing 160:93\u2013107","journal-title":"Neurocomputing"},{"issue":"3","key":"750_CR21","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1080\/00401706.1974.10489211","volume":"16","author":"PA Lachenbruch","year":"1974","unstructured":"Lachenbruch PA (1974) Discriminant analysis when the initial samples are misclassified II: non-random misclassification models. Technometrics 16(3):419\u2013424","journal-title":"Technometrics"},{"key":"750_CR22","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.neucom.2015.12.106","volume":"192","author":"J Bootkrajang","year":"2016","unstructured":"Bootkrajang J (2016) A generalised label noise model for classification in the presence of annotation errors. Neurocomputing 192:61\u201371","journal-title":"Neurocomputing"},{"key":"750_CR23","doi-asserted-by":"crossref","unstructured":"Du J, Cai Z (2015) Modelling class noise with symmetric and asymmetric distributions. In: AAAI, pp 2589\u20132595","DOI":"10.1609\/aaai.v29i1.9612"},{"key":"750_CR24","unstructured":"Schmidt M (2005) minFunc: unconstrained differentiable multivariate optimization in matlab. http:\/\/www.cs.ubc.ca\/~schmidtm\/Software\/minFunc.html"},{"key":"750_CR25","unstructured":"Chen Y, Ye X (2011) Projection onto a simplex. arXiv preprint arXiv:1101.6081"},{"issue":"20","key":"750_CR26","doi-asserted-by":"publisher","first-page":"11462","DOI":"10.1073\/pnas.201162998","volume":"98","author":"M West","year":"2001","unstructured":"West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, Zuzan H, Olson JA Jr, Marks JR, Nevins JR (2001) Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci USA 98(20):11462\u201311467","journal-title":"Proc Natl Acad Sci USA"},{"issue":"12","key":"750_CR27","doi-asserted-by":"publisher","first-page":"6745","DOI":"10.1073\/pnas.96.12.6745","volume":"96","author":"U Alon","year":"1999","unstructured":"Alon U, Barkai N, Notterman DA, Gishdagger K, Ybarradagger S, Mackdagger D, Levine AJ (1999) Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc Natl Acad Sci USA 96(12):6745\u20136750","journal-title":"Proc Natl Acad Sci USA"},{"key":"750_CR28","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1126\/science.286.5439.531","volume":"286","author":"TR Golub","year":"1999","unstructured":"Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286:531\u2013537","journal-title":"Science"},{"key":"750_CR29","volume-title":"UCI Machine Learning Repository","author":"D Dua","year":"2017","unstructured":"Dua D, Karra Taniskidou E (2017) UCI Machine Learning Repository. University of California, School of Information and Computer Science, Irvine, CA. http:\/\/archive.ics.uci.edu\/ml"},{"key":"750_CR30","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"},{"key":"750_CR31","first-page":"1871","volume":"9","author":"R-E Fan","year":"2008","unstructured":"Fan R-E, Chang K-W, Hsieh C-J, Wang X-R, Lin C-J (2008) LIBLINEAR: a library for large linear classification. J Mach Learn Res 9:1871\u20131874","journal-title":"J Mach Learn Res"}],"container-title":["Pattern Analysis and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10044-018-0750-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10044-018-0750-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10044-018-0750-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T22:43:10Z","timestamp":1661899390000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10044-018-0750-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,30]]},"references-count":31,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["750"],"URL":"https:\/\/doi.org\/10.1007\/s10044-018-0750-z","relation":{},"ISSN":["1433-7541","1433-755X"],"issn-type":[{"value":"1433-7541","type":"print"},{"value":"1433-755X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,30]]},"assertion":[{"value":"12 March 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 August 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}