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Features Reduction In Case Retrieval For Diabetes Dataset.

Bala, Abdalla Ali Abdalla (2007) Features Reduction In Case Retrieval For Diabetes Dataset. Masters thesis, Universiti Utara Malaysia.

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Abstract

In reality, the organizations often have the great quantity of data stored in the databases. The large size of data in terms of the number of attributes and objects make the analysis process becomes very difficult as the data are complex. In order to overcome this problem, the use of sufficient number of attributes and objects will contribute to get the best solution. There are many techniques which can be employed to reduce the number of attributes in the dataset. In this study, two techniques core using, namely rough set theory and Case-Based Reasoning were applied to the medical dataset.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Health, Diabetes, Diseases, Case Retrieval, Medical Data
Subjects: Q Science > Q Science (General)
Divisions: College of Arts and Sciences (CAS)
Depositing User: Mr Husni Ismail
Date Deposited: 14 Jun 2009 08:48
Last Modified: 24 Jul 2013 12:05
URI: http://etd.uum.edu.my/id/eprint/58

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