Features Reduction In Case Retrieval For Diabetes Dataset.
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 numb...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://etd.uum.edu.my/58/1/abdalla_ali.pdf http://etd.uum.edu.my/58/2/abdalla_ali.pdf http://etd.uum.edu.my/58/ |
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| Summary: | 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. |
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