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DOI: 10.14569/IJACSA.2014.050603
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Estimating Null Values in Database Using CBR and Supervised Learning Classification

Author 1: Khaled Nasser ElSayed

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 6, 2014.

  • Abstract and Keywords
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Abstract: Database and database systems have been used widely in almost, all life activities. Sometimes missed data items are discovered as missed or null values in the database tables. The presented paper proposes a design for a supervised learning system to estimate missed values found in the university database. The values of estimated data items or data it items used in estimation are numeric and not computed. The system performs data classification based on Case-Based Reasoning (CBR) to estimate loosed marks of students. A data set is used in training the system under the supervision of an expert. After training the system to classify and estimate null values under expert supervision, it starts classification and estimation of null data by itself.

Keywords: DataBase(DB);Data mining; Case-Based Reasoning (CBR); Classification;Null Values; Supervised Learning

Khaled Nasser ElSayed, “Estimating Null Values in Database Using CBR and Supervised Learning Classification” International Journal of Advanced Computer Science and Applications(IJACSA), 5(6), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050603

@article{ElSayed2014,
title = {Estimating Null Values in Database Using CBR and Supervised Learning Classification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050603},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050603},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {6},
author = {Khaled Nasser ElSayed}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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