{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T05:58:30Z","timestamp":1725602310150},"publisher-location":"Berlin, Heidelberg","reference-count":12,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642238772"},{"type":"electronic","value":"9783642238789"}],"license":[{"start":{"date-parts":[[2011,1,1]],"date-time":"2011-01-01T00:00:00Z","timestamp":1293840000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011]]},"DOI":"10.1007\/978-3-642-23878-9_26","type":"book-chapter","created":{"date-parts":[[2011,8,24]],"date-time":"2011-08-24T03:54:01Z","timestamp":1314158041000},"page":"212-219","source":"Crossref","is-referenced-by-count":6,"title":["Simplifying SVM with Weighted LVQ Algorithm"],"prefix":"10.1007","author":[{"given":"Marcin","family":"Blachnik","sequence":"first","affiliation":[]},{"given":"Miros\u0142aw","family":"Kordos","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"26_CR1","series-title":"Studies in Computational Intelligence Series","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-75390-2_7","volume-title":"Rule Extraction from Support Vector Machines","author":"M. Blachnik","year":"2008","unstructured":"Blachnik, M., Duch, W.: Prototype rules from SVM. In: Rule Extraction from Support Vector Machines. Studies in Computational Intelligence Series, vol.\u00a080, Springer, Heidelberg (2008)"},{"key":"26_CR2","first-page":"1858","volume-title":"IEEE International Joint Conference on Neural Networks","author":"W. Duch","year":"2001","unstructured":"Duch, W., Grudzi\u0144ski, K.: Prototype based rules - new way to understand the data. In: IEEE International Joint Conference on Neural Networks, pp. 1858\u20131863. IEEE Press, Washington, D.C (2001)"},{"key":"26_CR3","doi-asserted-by":"publisher","first-page":"1449","DOI":"10.1109\/TNN.2003.820828","volume":"14","author":"K. Lin","year":"2003","unstructured":"Lin, K., Lin, C.: A study on reduced support vector machines. IEEE Transactions on Neural Networks\u00a014, 1449\u20131459 (2003)","journal-title":"IEEE Transactions on Neural Networks"},{"key":"26_CR4","unstructured":"Sch\u00f6lkopf, B., Knirsch, P., Smola, A., Burges, C.: Fast approximation of support vector kernel expansions. Informatik Aktuell, Mustererkennung (1998)"},{"key":"26_CR5","unstructured":"Burges, C.: Simplified support vector decision rules. In: ICML, pp. 71\u201377 (1996)"},{"key":"26_CR6","first-page":"293","volume":"2","author":"T. Downs","year":"2001","unstructured":"Downs, T., Gates, K., Masters, A.: Exact simplification of support vector solutions. The JMLR\u00a02, 293\u2013297 (2001)","journal-title":"The JMLR"},{"key":"26_CR7","first-page":"603","volume":"4","author":"M. Wu","year":"2006","unstructured":"Wu, M., Sch\u00f6lkopf, B., Bakur, G.: A direct method for building sparse kernel learning. The JMLR\u00a04, 603\u2013624 (2006)","journal-title":"The JMLR"},{"key":"26_CR8","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"598","DOI":"10.1007\/978-3-540-24844-6_90","volume-title":"Artificial Intelligence and Soft Computing - ICAISC 2004","author":"N. Jankowski","year":"2004","unstructured":"Jankowski, N., Grochowski, M.: Comparison of instances seletion algorithms I. Algorithms survey. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol.\u00a03070, pp. 598\u2013603. Springer, Heidelberg (2004)"},{"key":"26_CR9","first-page":"408","volume":"15","author":"J. Kwok","year":"2003","unstructured":"Kwok, J., Tsang, I.: The pre-image problem in kernel methods. IEEE Transactions on Neural Networks\u00a015, 408\u2013415 (2003)","journal-title":"IEEE Transactions on Neural Networks"},{"key":"26_CR10","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/S0893-6080(01)00027-2","volume":"14","author":"F.S.H.K.G. Palm","year":"2001","unstructured":"Palm, F.S.H.K.G.: Three learning phases for radial-basis-function networks. Neural Networks\u00a014, 439\u2013458 (2001)","journal-title":"Neural Networks"},{"key":"26_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1007\/978-3-642-15825-4_31","volume-title":"Artificial Neural Networks \u2013 ICANN 2010","author":"M. Blachnik","year":"2010","unstructured":"Blachnik, M., Duch, W.: Improving accuracy of LVQ algorithm by instance weighting. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds.) ICANN 2010. LNCS, vol.\u00a06354, pp. 257\u2013266. Springer, Heidelberg (2010)"},{"key":"26_CR12","unstructured":"Merz, C., Murphy, P.: UCI repository of machine learning databases (1998-2004), \n                  \n                    http:\/\/www.ics.uci.edu\/~mlearn\/MLRepository.html"}],"container-title":["Lecture Notes in Computer Science","Intelligent Data Engineering and Automated Learning - IDEAL 2011"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-23878-9_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,3,31]],"date-time":"2019-03-31T20:55:29Z","timestamp":1554065729000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-23878-9_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011]]},"ISBN":["9783642238772","9783642238789"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-23878-9_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2011]]}}}