An extended k-means++ with mixed attributes for outlier detection. | |
| Author | Sarunya Kanjanawattana |
| Call Number | AIT Thesis no.CS-11-14 |
| Subject(s) | Accounting fraud Fraud Misleading financial statements Cluster analysis--Data processing |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. CS-11-14 |
| Abstract | Fraud detection becomes an important task nowadays especially a health insurance. Some developing country such as Thailand, we use human inspection and some heuristic rules to detect fraud on financial statements. That spends a lot of time to success and may provide incorrect results. This is a reason why we need effective fraud detection system to support the auditing of organization process. We proposed_ a new algorithm, called MixKmeans++, which is an extension of K-means++. The new algorithm can be applied to mixed numeric and categorical data. The limitation of K-means and K-means++ is to apply with only numeric data. Though, almost data in real world are combined by categorical and numeric data. This MixK-means++ algorithm can overcome this disadvantage. We compared the speed and performance of clustering between a standard K-means versus MixK-means++, and the results of outlier detection. MixK-means++ provided favor results even it worked with mixed attributes of data set. It was better both speed and performance than K-means. In order to compare the performance in outlier detection system, we can determine that MixK-means++ was also better in term of outlier detection because it provided higher detection rate than K-means even some cases of K-means might offer greater accuracy rate. |
| Year | 2011 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis : no. CS-11-14 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Guha, Sumanta; |
| Examination Committee(s) | Phan Minh Dung;Dailey, Matthew N.; |
| Scholarship Donor(s) | Royal Thai Government.; |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2011 |