| dc.contributor.author | Siti Aishah, Abdul Halim | |
| dc.date.accessioned | 2016-06-12T13:11:09Z | |
| dc.date.available | 2016-06-12T13:11:09Z | |
| dc.date.issued | 2015-05 | |
| dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/42039 | |
| dc.description | Access is limited to UniMAP community. | en_US |
| dc.description.abstract | This project is a study of using MME discretization method to generate rule for
thyroid data set. Discretization is simply a method to change the continuous data to
interval data set. Algorithm for finding the minimum entropy is use to discrete the
continuous data. Matlab and Weka software is use for the simulation. The result shown
the classification of rule that is generate from the discrete data set. Hence, the objective that been set at the beginning of this study have been achieve. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Universiti Malaysia Perlis (UniMAP) | en_US |
| dc.subject | Maximal marginal entropy (MME) | en_US |
| dc.subject | Thyroid | en_US |
| dc.subject | Thyroid data set | en_US |
| dc.subject | Discretization | en_US |
| dc.subject | Entropy | en_US |
| dc.subject | Generate rule | en_US |
| dc.title | Maximal Marginal Entropy (MME) discretization method to generate rule for Thyroid data set | en_US |
| dc.type | Learning Object | en_US |
| dc.contributor.advisor | Dr. Yasmin Yacob | en_US |
| dc.publisher.department | School of Computer and Communication Engineering | en_US |
