{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T18:03:19Z","timestamp":1771956199466,"version":"3.50.1"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2005,7,14]],"date-time":"2005-07-14T00:00:00Z","timestamp":1121299200000},"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":[[2005,12]]},"DOI":"10.1007\/s00521-005-0467-y","type":"journal-article","created":{"date-parts":[[2005,7,13]],"date-time":"2005-07-13T12:12:31Z","timestamp":1121256751000},"page":"310-318","source":"Crossref","is-referenced-by-count":192,"title":["Revisiting squared-error and cross-entropy functions for training neural network classifiers"],"prefix":"10.1007","volume":"14","author":[{"given":"Douglas M.","family":"Kline","sequence":"first","affiliation":[]},{"given":"Victor L.","family":"Berardi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2005,7,14]]},"reference":[{"key":"467_CR1","first-page":"691","volume-title":"AI2002: advances in artificial intelligence","author":"D Arotaritei","year":"2002","unstructured":"Arotaritei D, Negoita Gh M (2002) Optimisation of Recurrent NN by GA with Variable Length Genotype. In: McKay B, Slaney J (eds) AI2002: advances in artificial intelligence. Springer, Berlin Heidelberg New York, pp 691\u2013692"},{"key":"467_CR2","first-page":"52","volume-title":"Neural information processing systems","author":"EB Baum","year":"1988","unstructured":"Baum EB, Wilczek F (1988) Supervised learning of probability distributions by neural networks. In: Anderson D (ed) Neural information processing systems. American Institute of Physics, New York, pp 52\u201361"},{"issue":"3","key":"467_CR3","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1111\/j.1540-5915.1999.tb00902.x","volume":"30","author":"VL Berardi","year":"1999","unstructured":"Berardi VL, Zhang GQ (1999) The effect of misclassification costs on neural network classifiers. Decis Sci 30(3):659\u2013682","journal-title":"Decis Sci"},{"key":"467_CR4","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural networks for pattern recognition","author":"CM Bishop","year":"1995","unstructured":"Bishop CM (1995a) Neural networks for pattern recognition. Clarendon, Oxford"},{"key":"467_CR5","unstructured":"Bourlard H, Wellekens CJ (1989) Links between Markov models and multilayer perceptrons. In: Toretzky DS (ed) Advances in neural information processing systems, vol 1. Morgan Kaufmann, San Mateo, pp 502\u2013510"},{"key":"467_CR6","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/BF02551274","volume":"2","author":"G Cybenko","year":"1989","unstructured":"Cybenko G (1989) Approximation by superpositions of a sigmoidal function. Math Control Signals Syst 2:303\u2013314","journal-title":"Math Control Signals Syst"},{"key":"467_CR7","volume-title":"Pattern classification and scene analysis","author":"RO Duda","year":"1973","unstructured":"Duda RO, Hart P (1973) Pattern classification and scene analysis. Wiley, New York"},{"key":"467_CR8","first-page":"223","volume-title":"Artificial neural networks and expert systems","author":"F Fagarasan","year":"1995","unstructured":"Fagarasan F, Negoita Gh M (1995) A genetic-based method for learning the parameter of a fuzzy inference system. In: Kasabov N, Coghill G (eds) Artificial neural networks and expert systems. IEEE Computer Society, Los Alamitos, pp 223\u2013226"},{"issue":"2","key":"467_CR9","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 (1990) The upstart algorithm: a method for constructing and training feedforward neural networks. Neural Comput 2(2):198\u2013209","journal-title":"Neural Comput"},{"key":"467_CR10","unstructured":"Hampshire JB, Waibel A (1990) Connectionist architectures for multi-speaker phoneme recognition. In: Toretzky DS (ed) Advances in neural information processing systems, vol 2. Morgan Kaufmann, San Mateo, pp 203\u2013210"},{"key":"467_CR11","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/0893-6080(91)90009-T","volume":"4","author":"K Hornik","year":"1991","unstructured":"Hornik K (1991) Approximation capabilities of multilayer feedforward networks. Neural Netw 4:251\u2013257","journal-title":"Neural Netw"},{"key":"467_CR12","first-page":"49","volume":"1","author":"MS Hung","year":"1996","unstructured":"Hung MS, Hu MY, Patuwo BE, Shanker M (1996) Estimating posterior probabilities in classification problems with neural networks. Int J Comput Intell Organ 1:49\u201360","journal-title":"Int J Comput Intell Organ"},{"key":"467_CR13","first-page":"21921","volume":"22","author":"M Mezard","year":"1989","unstructured":"Mezard M, Nadal JP (1989) Learning in feedforward layered networks: the tiling algorithm. J Phys A 22:21921\u20132203","journal-title":"J Phys A"},{"key":"467_CR14","first-page":"175","volume-title":"Probability, random variables, and stochastic processes","author":"A Papoulis","year":"1964","unstructured":"Papoulis A (1964) Probability, random variables, and stochastic processes, 1st edn. McGraw Hill, New York, p 175","edition":"1"},{"key":"467_CR15","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1162\/neco.1991.3.4.461","volume":"3","author":"MD Richard","year":"1991","unstructured":"Richard MD, Lippmann RP (1991) Neural network classifiers estimate Bayesian a-posteriori probabilities. Neural comput 3:461\u2013483","journal-title":"Neural Comput"},{"key":"467_CR16","doi-asserted-by":"crossref","unstructured":"Rumelhart DE, Hinton GE, Williams RJ (1986a) Learning internal representations by error propagation. In: Rumelhart DE, McClelland JL, the PDP group (eds) Parallel distributed processing: exploration in the microstructure of cognition, Foundations. MIT Press, Cambridge, MA, pp 318\u2013362","DOI":"10.21236\/ADA164453"},{"key":"467_CR17","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart DE, Hinton GE, Williams RJ (1986b) Learning representation by backpropagating errors. Nat (Lond) 323:533\u2013536","journal-title":"Nat (Lond)"},{"issue":"1","key":"467_CR18","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1109\/72.80304","volume":"2","author":"PA Shoemaker","year":"1991","unstructured":"Shoemaker PA (1991) A note on least-squares learning procedures and classification by neural networks. IEEE Trans Neural Netw 2(1):158\u2013160","journal-title":"IEEE Trans Neural Netw"},{"issue":"4","key":"467_CR19","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1109\/72.80269","volume":"1","author":"EA Wan","year":"1990","unstructured":"Wan EA (1990) Neural network classification: a Bayesian interpretation. IEEE Trans Neural Netw 1(4):303\u2013375","journal-title":"IEEE Trans Neural Netw"},{"key":"467_CR20","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1162\/neco.1989.1.4.425","volume":"1","author":"H White","year":"1989","unstructured":"White H (1989) Learning in artificial neural networks: a statistical perspective. Neural Comput 1:425\u2013464","journal-title":"Neural Comput"},{"key":"467_CR21","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/0893-6080(90)90004-5","volume":"3","author":"H White","year":"1990","unstructured":"White H (1990) Connectionists nonparametric regression: multilayer feedforward networks can learn arbitrary mappings. Neural Netw 3:535\u2013549","journal-title":"Neural Netw"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-005-0467-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-005-0467-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-005-0467-y","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,27]],"date-time":"2024-01-27T21:06:02Z","timestamp":1706389562000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-005-0467-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,7,14]]},"references-count":21,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2005,12]]}},"alternative-id":["467"],"URL":"https:\/\/doi.org\/10.1007\/s00521-005-0467-y","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,7,14]]}}}