{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T14:56:38Z","timestamp":1761058598937},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2007,1,10]],"date-time":"2007-01-10T00:00:00Z","timestamp":1168387200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2007,11,19]]},"DOI":"10.1007\/s00521-006-0078-2","type":"journal-article","created":{"date-parts":[[2007,1,9]],"date-time":"2007-01-09T06:36:42Z","timestamp":1168324602000},"page":"19-25","source":"Crossref","is-referenced-by-count":5,"title":["Polynomial kernel adaptation and extensions to the SVM classifier learning"],"prefix":"10.1007","volume":"17","author":[{"given":"Ramy","family":"Saad","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saman K.","family":"Halgamuge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jason","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2007,1,10]]},"reference":[{"issue":"10","key":"78_CR1","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1093\/bioinformatics\/16.10.906","volume":"16","author":"TS Furey","year":"2000","unstructured":"Furey TS, Cristianini N, Duffy N, Bednarski DW, Schummer M, Haussler D (2000) Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 16(10):906\u2013914","journal-title":"Bioinformatics"},{"issue":"8","key":"78_CR2","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1093\/bioinformatics\/16.9.799","volume":"16","author":"A Zien","year":"2000","unstructured":"Zien A, Ratsch G, Mika S, Scholkopf B, Lengauer T, Muller KR (2000) Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics 16(8):799\u2013807","journal-title":"Bioinformatics"},{"issue":"1","key":"78_CR3","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1023\/A:1022936519097","volume":"17","author":"B Hammer","year":"2003","unstructured":"Hammer B, Gersmann K (2003) A note on the universal approximation capability of support vector machines. Neural Process Lett 17(1):43\u201345","journal-title":"Neural Process Lett"},{"issue":"1","key":"78_CR4","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1109\/72.822516","volume":"11","author":"SS Keerthi","year":"2000","unstructured":"Keerthi SS, Shevade SK, Bhattacharyya C, Murthy KRK (2000) A fast iterative nearest point algorithm for support vector machine classifier Design. IEEE Trans. Neural Netw 11(1):124\u2013136","journal-title":"IEEE Trans. Neural Netw"},{"key":"78_CR5","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1162\/089976601300014493","volume":"13","author":"SS Keerthi","year":"2001","unstructured":"Keerthi SS, Shevade SK, Bhattacharyya C, Murthy KRK (2001) Improvements to Platt\u2019s SMO algorithm for SVM classier design. Neural Comput 13:637\u2013649","journal-title":"Neural Comput"},{"key":"78_CR6","unstructured":"Campbell C, Cristianini N (1998). Simple learning algorithms for training support vector machines. Technical Report, University of Bristol. Available: http:\/\/www.svms.org\/training"},{"key":"78_CR7","unstructured":"Kecman V, Vogt M, Huang TM (2003) On the equality of Kernel AdaTron and sequential minimal optimisation in classification and regression tasks and alike algorithms for kernel machines. In: Proceedings of the 11th European symposium on artificial neural networks, Bruges, Belgium, Apr 2003"},{"key":"78_CR8","first-page":"161","volume":"1","author":"OL Mangasarian","year":"2001","unstructured":"Mangasarian OL, Musicant DR (2001) Lagrangian support vector machines. J Mach Learn Res 1:161\u2013177","journal-title":"J Mach Learn Res"},{"key":"78_CR9","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1018628609742","volume":"9","author":"JAK Suykens","year":"1999","unstructured":"Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9:293\u2013300","journal-title":"Neural Process Lett"},{"key":"78_CR10","doi-asserted-by":"crossref","unstructured":"Baesens B, Viaene S, Van Gestel T, Suykens JAK, Dedene G, De Moor B, Vanthienen J (2000) An empirical assessment of kernel type performance for least squares support vector machine classifiers. In: Proc. 4th int. conf. knowledge-based intelligent engineering systems and allied technologies, 2000.","DOI":"10.1109\/KES.2000.885819"},{"key":"78_CR11","unstructured":"Cristianini N, Campbell C, Shawe-Taylor J (1999) Dynamically adapting kernels in support vector machines. In: Kearns MS, Solla SA, Cohn DA (eds) Advances in neural information processing systems 11. MIT Press, Cambridge"},{"key":"78_CR12","unstructured":"Askew A, Miettinen H, Padley B (2003) Event selection using adaptive gaussian kernels. In: Proceedings of statistical problems in particle physics, astrophysics, and cosmology, Stanford, CA, Sep 2003"},{"issue":"3","key":"78_CR13","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1109\/TIT.1972.1054809","volume":"18","author":"GW Gates","year":"1972","unstructured":"Gates GW (1972) The Reduced Nearest Neighbor Rule. IEEE Trans Inf Theory 18(3):431\u2013433","journal-title":"IEEE Trans Inf Theory"},{"key":"78_CR14","unstructured":"Thrun SB, Bala J, Bloedorn E, Bratko I, Cestnik B, Cheng J, et\u00a0al. (1991). The MONK\u2019s problems\u2013a performance comparison of different learning algorithms. Technical Report CS-CMU-91\u2013197, Carnegie Mellon University"},{"issue":"22","key":"78_CR15","doi-asserted-by":"crossref","first-page":"12079","DOI":"10.1073\/pnas.210134797","volume":"97","author":"G Getz","year":"2000","unstructured":"Getz G, Levine E, Domany E (2000). Coupled two-way clustering analysis of gene microarray data. PNAS: Cell Biol Genet 97(22):12079\u201312084","journal-title":"PNAS: Cell Biol Genet"},{"key":"78_CR16","volume-title":"Statistical learning theory","author":"VN Vapnik","year":"1998","unstructured":"Vapnik VN (1998) Statistical learning theory. Wiley, New York"},{"key":"78_CR17","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 (2000). An introduction to support vector machines: and other kernel-based learning methods. Cambridge Press, Cambridge"},{"key":"78_CR18","volume-title":"Neural and adaptive systems: fundamentals through simulations","author":"JC Principe","year":"1999","unstructured":"Principe JC, Euliano NR, Lefebvre WC (1999). Neural and adaptive Systems: fundamentals through simulations. Wiley, New York"},{"key":"78_CR19","volume-title":"Dimensional analysis","author":"GI Barenblatt","year":"1987","unstructured":"Barenblatt GI (1987) Dimensional analysis. Gordon & Breach, New York"},{"key":"78_CR20","doi-asserted-by":"crossref","unstructured":"Halgamuge SK, Poechmueller W, Glesner M (1995) An alternative approach for generation of membership functions and fuzzy rules based on radial and cubic basis function networks. Int J Approx Reason 12(3\u20134):279\u2013298","DOI":"10.1016\/0888-613X(94)00032-X"},{"issue":"4","key":"78_CR21","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/91.544301","volume":"4","author":"T Hollstein","year":"1996","unstructured":"Hollstein T, Halgamuge SK, Glesner M (1996) Computer-aided design of fuzzy systems based on generic VHDL specifications. IEEE Trans Fuzzy Syst 4(4):403\u2013417","journal-title":"IEEE Trans Fuzzy Syst"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-006-0078-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-006-0078-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-006-0078-2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T22:06:55Z","timestamp":1559081215000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-006-0078-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,1,10]]},"references-count":21,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2007,11,19]]}},"alternative-id":["78"],"URL":"https:\/\/doi.org\/10.1007\/s00521-006-0078-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2007,1,10]]}}}