Naive-bayes inspired effective pre-conditioner for speeding-up logistic regression Zaidi, Nayyar A., Carman, Mark J., Cerquides, Jesus and Webb, Geoffrey I. 2014, Naive-bayes inspired effective pre-conditioner for speeding-up logistic regression, in ICDM 2014 : Proceedings of the 14th IEEE International Conference on Data Mining, IEEE, Piscataway, N.J., pp. 1097-1102, doi: 10.1109/icdm.2014.53. Attached Files Name Description MIMEType Size Downloads nayyar-naivebayes-post-2014.pdf Accepted version application/pdf 3.77MB 4 Title Naive-bayes inspired effective pre-conditioner for speeding-up logistic regression Author(s) Zaidi, Nayyar A. orcid.org/0000-0003-4024-2517 Carman, Mark J. Cerquides, Jesus Webb, Geoffrey I. Conference name Data Mining. International Conference (14th : 2014 : Shenzhen, China) Conference location Shenzhen, China Conference dates 2014/12/14 - 2014/12/17 Title of proceedings ICDM 2014 : Proceedings of the 14th IEEE International Conference on Data Mining Editor(s) Kumar, R. Toivonen, H. Pei, J. Huang, J. Z. Wu, X. Publication date 2014 Start page 1097 End page 1102 Total pages 6 Publisher IEEE Place of publication Piscataway, N.J. Keyword(s) classification logistic regression pre-conditioning weighted naive Bayes stochastic gradient descent discriminative/generative learning ISBN 9781479943029 ISSN 1550-4786 2374-8486 Language eng DOI 10.1109/icdm.2014.53 Indigenous content off HERDC Research category E1.1 Full written paper - refereed Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30135391 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 03 Mar 2020, 12:54:30 EST Wed, 04 Mar 2020, 04:01:36 EST Wed, 04 Mar 2020, 07:16:33 EST Wed, 04 Mar 2020, 10:07:12 EST Thu, 05 Mar 2020, 05:04:01 EST Tue, 24 Mar 2020, 14:37:59 EST Tue, 24 Mar 2020, 14:46:08 EST Tue, 24 Mar 2020, 14:46:51 EST Tue, 31 Mar 2020, 12:54:52 EST Sat, 28 Nov 2020, 01:42:05 EST Sat, 09 Jan 2021, 01:36:30 EST Filtered Full Citation counts:   Cited 8 times in TR Web of Science Cited 9 times in Scopus Search Google Scholar Access Statistics: 100 Abstract Views, 6 File Downloads  -  Detailed Statistics Created: Wed, 04 Mar 2020, 10:07:12 EST

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