Openly accessible

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 1

Title Naive-bayes inspired effective pre-conditioner for speeding-up logistic regression
Author(s) Zaidi, Nayyar A.ORCID iD for 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

Connect to link resolver
 
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
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 44 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Wed, 04 Mar 2020, 10:07:12 EST

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.