A Genetic Algorithm Approach for Non-Ignorable Missing Data
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10.5120/2419-3237 |
R.Devi Priya, S.Kuppuswami and S.Makesh Kumar. Article: A Genetic Algorithm Approach for Non-Ignorable Missing Data. International Journal of Computer Applications 20(4):37-41, April 2011. Full text available. BibTeX
@article{key:article,
author = {R.Devi Priya and S.Kuppuswami and S.Makesh Kumar},
title = {Article: A Genetic Algorithm Approach for Non-Ignorable Missing Data},
journal = {International Journal of Computer Applications},
year = {2011},
volume = {20},
number = {4},
pages = {37-41},
month = {April},
note = {Full text available}
}
Abstract
The databases store data that may be subjected to missing values either in data acquisition or data storage process. The proposed approach uses the widely used optimization technique called genetic algorithm for the NMAR (Not Missing At Random) missing mechanism which prevails more in real life that are non-ignorable. Since the non-ignorable mechanism needs prior basic knowledge about the data that is supposed to be missing and have to make assumptions, Genetic algorithm (GA) suits well for this problem which derives solution based on the previously observed data. The empirical results show that Genetic Algorithm has better efficiency when compared with some of the traditional methods.
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