Missing Data Estimation using Principle Component Analysis and Autoassociative Neural Networks
Three new methods are used for estimating missing data in a database using Neural Networks, Principal Component Analysis and Genetic Algorithms are presented. The proposed methods are tested on a set of data obtained from the South African Antenatal Survey. The data is a collection of demographic pr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
International Institute of Informatics and Cybernetics
2009-06-01
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| Series: | Journal of Systemics, Cybernetics and Informatics |
| Subjects: | |
| Online Access: | http://www.iiisci.org/Journal/CV$/sci/pdfs/KS628XI.pdf
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