{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T23:27:26Z","timestamp":1725492446463},"publisher-location":"Berlin, Heidelberg","reference-count":20,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540724315"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1007\/978-3-540-72432-2_11","type":"book-chapter","created":{"date-parts":[[2007,9,19]],"date-time":"2007-09-19T04:32:12Z","timestamp":1190176332000},"page":"99-108","source":"Crossref","is-referenced-by-count":1,"title":["Fuzzy Rules Extraction from Support Vector Machines for Multi-class Classification"],"prefix":"10.1007","author":[{"given":"Adriana","family":"Costa F. Chaves","sequence":"first","affiliation":[]},{"given":"Marley Maria B. R.","family":"Vellasco","sequence":"additional","affiliation":[]},{"given":"Ricardo","family":"Tanscheit","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"11_CR1","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511801389","volume-title":"An Introduction to Support Vector Machines and other kernel - based learning methods","author":"N. Cristianini","year":"2000","unstructured":"Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and other kernel - based learning methods. Cambridge University Press, Cambridge (2000), http:\/\/www.support-vector.net"},{"key":"11_CR2","unstructured":"Gunn, S.: Support Vector Machines for Classification and Regression. ISIS Technical Report (1998), http:\/\/www.isis.ecs.soton.ac.uk\/research\/svm\/"},{"key":"11_CR3","volume-title":"Neural Networks - A Comprehensive Foundation","author":"S. Haykin","year":"1999","unstructured":"Haykin, S.: Neural Networks - A Comprehensive Foundation. Macmillan College Publishing Company, Basingstoke (1999)"},{"key":"11_CR4","volume-title":"Learning with Kernels","author":"B. Scholkopf","year":"2002","unstructured":"Scholkopf, B., Smola, A.J.: Learning with Kernels. MIT Press, Cambridge (2002)"},{"issue":"5","key":"11_CR5","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1109\/72.788640","volume":"10","author":"V.N. Vapnik","year":"1999","unstructured":"Vapnik, V.N.: An Overview of Statistical Learning Theory. IEEE Transactions on Neural Networks\u00a010(5), 988\u2013999 (1999)","journal-title":"IEEE Transactions on Neural Networks"},{"key":"11_CR6","volume-title":"Statistical Learning Theory","author":"V.N. Vapnik","year":"1998","unstructured":"Vapnik, V.N.: Statistical Learning Theory. John Wiley & Sons, Chichester (1998)"},{"key":"11_CR7","first-page":"281","volume-title":"Advances in Neural Information Processing System 9","author":"V.N. Vapnik","year":"1997","unstructured":"Vapnik, V.N., Golowich, S.E., Smola, A.: Support vector method for function approximation, regression estimation, and signal processing. In: Mozer, M.C., Jordan, M.I., Petsche, T. (eds.) Advances in Neural Information Processing System 9, pp. 281\u2013287. Morgan Kaufmann, San Mateo (1997)"},{"issue":"5","key":"11_CR8","doi-asserted-by":"publisher","first-page":"1048","DOI":"10.1109\/72.788645","volume":"10","author":"H.D. Drucker","year":"1999","unstructured":"Drucker, H.D., Wu, D.H., Vapnik, V.N.: Support vector machines for spam categorization. IEEE Trans. on Neural Networks\u00a010(5), 1048\u20131054 (1999)","journal-title":"IEEE Trans. on Neural Networks"},{"key":"11_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/BFb0026683","volume-title":"Machine Learning: ECML-98","author":"T. Joachims","year":"1998","unstructured":"Joachims, T.: Text categorization with support vector machines: Learning with many relevant features. In: N\u00e9dellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol.\u00a01398, pp. 137\u2013142. Springer, Heidelberg (1998)"},{"key":"11_CR10","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1073\/pnas.97.1.262","volume":"97","author":"M.P. Brown","year":"2000","unstructured":"Brown, M.P., et al.: Knowledge-based analysis of microarray gene expression data by using support vector machines. Proceedings of The National Academy of Sciences of The United States of America\u00a097, 262\u2013267 (2000)","journal-title":"Proceedings of The National Academy of Sciences of The United States of America"},{"key":"11_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","DOI":"10.1007\/BFb0013568","volume-title":"Artificial Neural Networks - ICANN\u201997","author":"K.R. M\u00fcller","year":"1997","unstructured":"M\u00fcller, K.R., et al.: Predicting time series with support vector machines. In: Gerstner, W., et al. (eds.) ICANN 1997. LNCS, vol.\u00a01327, Springer, Heidelberg (1997)"},{"key":"11_CR12","unstructured":"Fu, X., et al.: Extracting the Knowledge Embedded in Support Vector Machines. In: International Joint Conference on Neural Networks (IJCNN\u201904), CDROM, Budapest, July 25-29 (2004)"},{"key":"11_CR13","unstructured":"Nunez, H., Angulo, C., Catal\u00e1, A.: Rule Extraction From support vectors machines. In: European Symposium on Artificial Neural Networks (ESANN), pp. 107\u2013112 (2002)"},{"issue":"2","key":"11_CR14","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1109\/72.991427","volume":"13","author":"C.-W. Hsu","year":"2002","unstructured":"Hsu, C.-W., Lin, C.-J.: A Comparison on Methods for Multi-class Support Vector Machines. IEEE Transaction on Neural Networks\u00a013(2), 415\u2013425 (2002)","journal-title":"IEEE Transaction on Neural Networks"},{"key":"11_CR15","unstructured":"Crammer, K., Singer, Y.: On the learnability and design of output codes for multiclass problems. In: Computational Learning Theory, pp. 35\u201346 (2000)"},{"key":"11_CR16","unstructured":"Weston, J., Watkins, C.: Multi-class Support Vector Machines. Technical report CSD-TR-98-04, Royal Holloway (1998)"},{"key":"11_CR17","first-page":"101","volume":"5","author":"R. Rifkin","year":"2004","unstructured":"Rifkin, R., Klautau, A.: In Defense of One-Vs-All Classification. Journal of Machine Learning Research\u00a05, 101\u2013141 (2004)","journal-title":"Journal of Machine Learning Research"},{"key":"11_CR18","unstructured":"Abe, S., Inoue, T.: Fuzzy Support Vector Machines for Multiclass Problems. In: European Symposium on Artificial Neural Networks proceedings (ESANN), pp. 113\u2013118 (2002)"},{"key":"11_CR19","first-page":"225","volume-title":"Advances in kernel methods: Support vector learning","author":"U.H.-G. Kressel","year":"1999","unstructured":"Kressel, U.H.-G.: Pairwise classification and support vector machines. In: Sch\u00f6lkopf, B., Burges, C.J.C., Smola, A.J. (eds.) Advances in kernel methods: Support vector learning, pp. 225\u2013268. MIT Press, Cambridge (1999)"},{"key":"11_CR20","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1109\/ICHIS.2005.51","volume-title":"5th Int. Conf. on Hybrid Intelligent Systems (HIS05)","author":"A. Chaves","year":"2005","unstructured":"Chaves, A., Vellasco, M.M.B.R., Tanscheit, R.: Fuzzy Rule Extraction from Support Vector Machines. In: Nejah, N., et al. (eds.) 5th Int. Conf. on Hybrid Intelligent Systems (HIS05), Pontif\u00edcia Universidade Cat\u00f3lica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ, Brazil, November 6-9 2005, pp. 335\u2013340. IEEE, Los Alamitos (2005)"}],"container-title":["Advances in Soft Computing","Analysis and Design of Intelligent Systems using Soft Computing Techniques"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-72432-2_11.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,19]],"date-time":"2020-11-19T05:33:20Z","timestamp":1605764000000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-72432-2_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"ISBN":["9783540724315"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-72432-2_11","relation":{},"subject":[]}}