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9th International Conference on Information Technology (ICIT'06)
A comparative analysis of discretization methods for Medical Datamining with Na?ve Bayesian classifier
Bhubaneswar, India
December 18-December 21
ISBN: 0-7695-2635-7
ASCII Text
x 
 
Ranjit Abraham, Jay B.Simha, S.S Iyengar, "A comparative analysis of discretization methods for Medical Datamining with Na?ve Bayesian classifier," Information Technology, International Conference on, pp. 235-236, 9th International Conference on Information Technology (ICIT'06), 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICIT.2006.5,
author = {Ranjit Abraham and Jay B.Simha and S.S Iyengar},
title = {A comparative analysis of discretization methods for Medical Datamining with Na?ve Bayesian classifier},
journal ={Information Technology, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2635-7},
pages = {235-236},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICIT.2006.5},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Information Technology, International Conference on
TI - A comparative analysis of discretization methods for Medical Datamining with Na?ve Bayesian classifier
SN - 0-7695-2635-7
SP235
EP236
A1 - Ranjit Abraham,
A1 - Jay B.Simha,
A1 - S.S Iyengar,
PY - 2006
KW - null
VL - 0
JA - Information Technology, International Conference on
ER -
 
Ranjit Abraham, TocH Institute of Sci. and Tech., Arakkunnam, Kerala,India
Jay B.Simha, ABIBA Systems, Bangalore, INDIA
S.S Iyengar, Louisiana State University, Baton Rouge
Naive Bayes classifier has gained wide popularity as a probability-based classification method despite its assumption that attributes are conditionally mutually independent given the class label. This paper makes a study into discretization techniques to improve the classification accuracy of Na?ve Bayes with respect to medical datasets. Our experimental results suggest that on an average, with Minimum Description Length (MDL) discretization the Na?ve Bayes Classifier seems to be the best performer compared to popular variants of Na?ve Bayes as well as some popular non-Na?ve Bayes statistical classifiers.
Citation:
Ranjit Abraham, Jay B.Simha, S.S Iyengar, "A comparative analysis of discretization methods for Medical Datamining with Na?ve Bayesian classifier," icit, pp.235-236, 9th International Conference on Information Technology (ICIT'06), 2006
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