{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T18:34:06Z","timestamp":1715279646843},"reference-count":14,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2010,6,3]],"date-time":"2010-06-03T00:00:00Z","timestamp":1275523200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cogn Comput"],"published-print":{"date-parts":[[2010,12]]},"DOI":"10.1007\/s12559-010-9051-6","type":"journal-article","created":{"date-parts":[[2010,6,2]],"date-time":"2010-06-02T14:20:06Z","timestamp":1275488406000},"page":"285-290","source":"Crossref","is-referenced-by-count":16,"title":["Multiclass Pattern Recognition Extension for the New C-Mantec Constructive Neural Network Algorithm"],"prefix":"10.1007","volume":"2","author":[{"given":"Jos\u00e9 L.","family":"Subirats","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 M.","family":"Jerez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Iv\u00e1n","family":"G\u00f3mez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leonardo","family":"Franco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2010,6,3]]},"reference":[{"key":"9051_CR1","volume-title":"Neural Networks: A Comprehensive Foundation","author":"S Haykin","year":"1994","unstructured":"Haykin S. Neural networks: a comprehensive foundation. NY: Macmillan\/IEEE Press;1994."},{"key":"9051_CR2","unstructured":"Lawrence S, Giles CL, Tsoi AC. What size neural network gives optimal generalization ? Convergence properties of backpropagation. In: Technical report UMIACS-TR-96-22 and CS-TR-3617, Institute for Advanced Computer Studies, Univ. of Maryland. 1996."},{"key":"9051_CR3","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/s11063-009-9108-2","volume":"30","author":"I G\u00f3mez","year":"2009","unstructured":"G\u00f3mez I, Franco L, Jerez JM. Neural network architecture selection: Can function complexity help? Neural Process Lett. 2009;30:71\u201387.","journal-title":"Neural Process Lett"},{"key":"9051_CR4","doi-asserted-by":"crossref","unstructured":"Franco L, Elizondo D, Jerez JM, editors. Constructive neural networks. Berlin: Springer; 2010.","DOI":"10.1007\/978-3-642-04512-7"},{"key":"9051_CR5","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/BF01189880","volume":"12","author":"FJ Smieja","year":"1993","unstructured":"Smieja FJ. Neural network constructive algorithms: trading generalization for learning efficiency? Circuits Syst Signal Process. 1993;12:331\u201374.","journal-title":"Circuits Syst Signal Process"},{"key":"9051_CR6","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1504\/IJICA.2007.013397","volume":"1","author":"MC do Carmo Nicoletti","year":"2007","unstructured":"do Carmo Nicoletti MC, Bertini JR. An empirical evaluation of constructive neural network algorithms in classification tasks. Int J Innov Comput Appl. 2007;1:2\u201313.","journal-title":"Int J Innov Comput Appl"},{"key":"9051_CR7","doi-asserted-by":"crossref","first-page":"2191","DOI":"10.1088\/0305-4470\/22\/12\/019","volume":"22","author":"M Mezard","year":"1989","unstructured":"Mezard M, Nadal JP. Learning in feedforward layered networks: the tiling algorithm. J Phys A. 1989;22:2191\u2013204.","journal-title":"J Phys A"},{"key":"9051_CR8","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1162\/neco.1990.2.2.198","volume":"2","author":"M Frean","year":"1990","unstructured":"Frean M. The upstart algorithm: a method for constructing and training feedforward neural networks. Neural Comput. 1990;2:198\u2013209.","journal-title":"Neural Comput"},{"key":"9051_CR9","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1109\/72.839013","volume":"11","author":"R Parekh","year":"2000","unstructured":"Parekh R, Yang J, Honavar V. Constructive neural-network learning algorithms for pattern classification. IEEE Trans Neural Netw. 2000;11:436\u201351.","journal-title":"IEEE Trans Neural Netw"},{"key":"9051_CR10","doi-asserted-by":"crossref","first-page":"3188","DOI":"10.1109\/TCSI.2008.923432","volume":"55","author":"JL Subirats","year":"2008","unstructured":"Subirats JL, Jerez JM, Franco L. A new decomposition algorithm for threshold synthesis and generalization of Boolean functions. IEEE Trans Circuits Syst I. 2008;55:3188\u201396.","journal-title":"IEEE Trans Circuits Syst I"},{"key":"9051_CR11","first-page":"418","volume":"40","author":"G Ou","year":"2007","unstructured":"Ou G, Murphey YL. Multi-class pattern classification using neural networks. Pattern Recognit. 2007;40:418.","journal-title":"Pattern Recognit"},{"key":"9051_CR12","unstructured":"Subirats JL, Jerez JM, Franco L. A local stable learning rule and global competition for generating compact neural network architectures with good generalization abilities: the C-Mantec algorithm. Submitted. 2010."},{"key":"9051_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1021\/ci0342472","volume":"44","author":"DM Hawkins","year":"2004","unstructured":"Hawkins DM. The problem of overfitting. J Chem Info Comput Sci. 2004; 44:1\u201312.","journal-title":"J Chem Info Comput Sci"},{"key":"9051_CR14","unstructured":"Prechelt L. Proben 1\u2014A set of benchmarks and benchmarking rules for neural network training algorithms. Technical Report. 1994."}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-010-9051-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s12559-010-9051-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-010-9051-6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,2]],"date-time":"2019-06-02T12:36:48Z","timestamp":1559479008000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s12559-010-9051-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,6,3]]},"references-count":14,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2010,12]]}},"alternative-id":["9051"],"URL":"https:\/\/doi.org\/10.1007\/s12559-010-9051-6","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"value":"1866-9956","type":"print"},{"value":"1866-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,6,3]]}}}