Fraud detection process in data mining using adaptive and rule learning algorithm techniques
| dc.contributor.author | Kornyo, Oliver | |
| dc.date.accessioned | 2016-07-26T09:02:17Z | |
| dc.date.accessioned | 2023-04-19T21:02:29Z | |
| dc.date.available | 2016-07-26T09:02:17Z | |
| dc.date.available | 2023-04-19T21:02:29Z | |
| dc.date.issued | 2014-03-26 | |
| dc.description | A thesis submitted to the Department of Computer Science, Kwame Nkrumah University of Science and Technology in partial fulfillment for the degree of Master of Philosophy in Information Technology, 2014 | en_US |
| dc.description.abstract | The main objective of this study was to apply adaptive and rule learning techniques in data mining for fraud detection in Electricity Company of Ghana (ECG). This work combines the rule learning techniques in supervised and unsupervised fraud detection in data set and considers the behavior of data set.... | en_US |
| dc.description.sponsorship | KNUST | en_US |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/8869 | |
| dc.language.iso | en | en_US |
| dc.title | Fraud detection process in data mining using adaptive and rule learning algorithm techniques | en_US |
| dc.type | Thesis | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Kornyo Oliver.pdf
- Size:
- 13.07 MB
- Format:
- Adobe Portable Document Format
- Description:
- Full Thesis