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|Title:||An Investigation into Error Propagation Chained Model||Contributor(s):||Gao, Junbin (author)||Publication Date:||2003||Handle Link:||https://hdl.handle.net/1959.11/5665||Abstract:||In this paper we describe several possible approaches for estimating uncertainty in the target output in the chained models. We introduce the approaches from the simple linear model, the nonlinear to the Bayesian modelling method including Markov Chain Monte Carlo simulation algorithm. Under several rough assumptions we derive some approximated estimation formulas. The estimated formulas strongly depend not only on the characteristic property of the noises existed in both input pattern and output pattern but also on the given model structure f(x,w) as well as the training dataset.||Publication Type:||Conference Publication||Conference Name:||2003 International Conference on Machine Learning and Cybernetics, Xi'an, China, 2 - 5 November, 2003||Conference Details:||2003 International Conference on Machine Learning and Cybernetics, Xi'an, China, 2 - 5 November, 2003||Source of Publication:||Proceedings of the 2nd International Conference on Machine Learning and Cybernetics, p. 1168-1173||Publisher:||IEEE: Institute of Electrical and Electronics Engineers Systems||Place of Publication:||United States of America||Field of Research (FOR):||080108 Neural, Evolutionary and Fuzzy Computation||Socio-Economic Outcome Codes:||890205 Information Processing Services (incl. Data Entry and Capture)||HERDC Category Description:||E4 Editorship of Scholarly Conference Proceedings||Other Links:||http://trove.nla.gov.au/work/17536094||Statistics to Oct 2018:||Visitors: 73
|Appears in Collections:||Conference Publication|
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