{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:59:30Z","timestamp":1775325570926,"version":"3.50.1"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030736880","type":"print"},{"value":"9783030736897","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-73689-7_56","type":"book-chapter","created":{"date-parts":[[2021,4,15]],"date-time":"2021-04-15T11:29:51Z","timestamp":1618486191000},"page":"583-592","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Incremental Fuzzy Learning Approach for Online Classification of Data Streams"],"prefix":"10.1007","author":[{"given":"Vladyslav","family":"Yavtukhovskyi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rami","family":"Abukhader","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nils","family":"Tillaeus","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,16]]},"reference":[{"key":"56_CR1","unstructured":"Murphey, Y., Chen, T.: Incremental learning in a fuzzy intelligent system. In: Proceedings of the 16th International Joint Conference on Artificial Intelligence, IJCAI, vol. 2, pp. 1376\u20131384. Morgan Kaufmann Publishers Inc. (1999)"},{"issue":"1","key":"56_CR2","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/0921-8890(95)00034-D","volume":"16","author":"P Reignier","year":"1995","unstructured":"Reignier, P.: Supervised incremental learning of fuzzy rules. Robot. Auton. Syst. 16(1), 57\u201371 (1995)","journal-title":"Robot. Auton. Syst."},{"issue":"1","key":"56_CR3","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/S0165-0114(02)00060-X","volume":"132","author":"MS Mouchaweh","year":"2002","unstructured":"Mouchaweh, M.S., Devillez, A., Lecolier, G.V., Billaudel, P.: Incremental learning in fuzzy pattern matching. Fuzzy Sets Syst. 132(1), 49\u201362 (2002)","journal-title":"Fuzzy Sets Syst."},{"key":"56_CR4","unstructured":"Visa, S., Ralescu, A.: Towards online learning of a fuzzy classifier. In: Meeting of the North American Fuzzy Information Processing Society, Cincinnati, USA (2005)"},{"issue":"12","key":"56_CR5","doi-asserted-by":"publisher","first-page":"2389","DOI":"10.1007\/s00500-010-0668-x","volume":"15","author":"A Orriols-Puig","year":"2011","unstructured":"Orriols-Puig, A., Casillas, J.: Fuzzy knowledge representation study for incremental learning in data streams and classification problems. Soft. Comput. 15(12), 2389\u20132414 (2011)","journal-title":"Soft. Comput."},{"key":"56_CR6","doi-asserted-by":"crossref","unstructured":"G\u00e1mez, J.C., Garc\u00eda, D., Gonz\u00e1lez, A., P\u00e9rez, R.: On the use of an incremental approach to learn fuzzy classification rules for big data problems. In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1413\u20131420. IEEE (2016)","DOI":"10.1109\/FUZZ-IEEE.2016.7737855"},{"key":"56_CR7","doi-asserted-by":"crossref","unstructured":"Romero-Zaliz, R., Gonz\u00e1lez, A., P\u00e9rez, R.: Incremental fuzzy learning algorithms in big data problems. a study on the size of learning subsets. In:\u00a02017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1\u20136. IEEE (2017)","DOI":"10.1109\/FUZZ-IEEE.2017.8015671"},{"issue":"9","key":"56_CR8","doi-asserted-by":"publisher","first-page":"1109","DOI":"10.1080\/00207720010015735","volume":"32","author":"N Xiong","year":"2001","unstructured":"Xiong, N.: Evolutionary learning of rule premises for fuzzy modelling. Int. J. Syst. Sci. 32(9), 1109\u20131118 (2001)","journal-title":"Int. J. Syst. Sci."},{"key":"56_CR9","unstructured":"UCI machine learning repository. https:\/\/archive.ics.uci.edu\/ml\/index.php. Accessed 31 Oct 2020"},{"issue":"6","key":"56_CR10","doi-asserted-by":"publisher","first-page":"1414","DOI":"10.1109\/21.199466","volume":"22","author":"LX Wang","year":"1992","unstructured":"Wang, L.X., Mendel, J.M.: Generating fuzzy rules by learning from examples. IEEE Trans. Syst. Man Cybern. 22(6), 1414\u20131427 (1992)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"issue":"6","key":"56_CR11","first-page":"148","volume":"9","author":"G Ayyappan","year":"2019","unstructured":"Ayyappan, G.: Meta classifications for caesarian section classification dataset data set. Indian J. Comput. Sci. Eng. 9(6), 148\u2013150 (2019). Chennai, India","journal-title":"Indian J. Comput. Sci. Eng."},{"key":"56_CR12","unstructured":"Kwedlo, W, Kr\u0119towski, M.: Discovery of decision rules from databases: An Evolutionary Approach. Technical University of Bialystok, Bia\u0142ystok, Poland (2006)"},{"key":"56_CR13","unstructured":"Mansourifar, H., Shi, W.: Toward efficient breast cancer diagnosis and survival prediction using L-Perceptron. University of Houston Houston, Texas (2018)"},{"key":"56_CR14","doi-asserted-by":"crossref","unstructured":"Krogel, M.A., Rawles, S., \u017delezn\u00fd, F., Flach, P.A., Lavra\u010d, N., Wrobel, S.: Comparative evaluation of approaches to propositionalization. In: Proceedings of the 13th International Conference on ILP, Szeged (2003)","DOI":"10.1007\/978-3-540-39917-9_14"},{"key":"56_CR15","unstructured":"Agrawal, D., Dahiya, P.: Comparisons of classification algorithms on seeds dataset using machine learning algorithm. An Int. J. Adv. Comput. Technol. 7, 2760\u20132765 (2018)"},{"key":"56_CR16","doi-asserted-by":"crossref","unstructured":"D\u017eeroski, S., \u017denko, B.: Stacking with multi-response model trees. In: International Workshop on Multiple Classifier Systems. Springer, Heidelberg (2002)","DOI":"10.1007\/3-540-45428-4_20"},{"key":"56_CR17","unstructured":"Hall, M.A.: Feature selection for discrete and numeric class machine learning (1999)"},{"key":"56_CR18","first-page":"10","volume":"7","author":"YD Austria","year":"2019","unstructured":"Austria, Y.D., Jay-ar, P.L., Maria, L.B.S., Jr., Goh, J.E.E., Goh, M.L.I., Vicente, H.N.: Comparison of machine learning algorithms in breast cancer prediction using the coimbra dataset. Cancer 7, 10 (2019)","journal-title":"Cancer"},{"key":"56_CR19","doi-asserted-by":"crossref","unstructured":"Kumar, C., Dudyala, A. K.: Bank note authentication using decision tree rules and machine learning techniques. In: International Conference on Advances in Computer Engineering and Applications, pp. 310\u2013314 (2015)","DOI":"10.1109\/ICACEA.2015.7164721"},{"issue":"1","key":"56_CR20","first-page":"53","volume":"29","author":"SB Kotsiantis","year":"2005","unstructured":"Kotsiantis, S.B.: Logitboost of simple Bayesian classifier. Informatica 29(1), 53\u201359 (2005)","journal-title":"Informatica"}],"container-title":["Advances in Intelligent Systems and Computing","Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-73689-7_56","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,15]],"date-time":"2021-04-15T14:04:30Z","timestamp":1618495470000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-73689-7_56"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030736880","9783030736897"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-73689-7_56","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"16 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SoCPaR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Soft Computing and Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socpar2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mirlabs.net\/socpar20\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}