| Asian Ethnic Group Classification Model Using Data Mining. |
|
Yoon Geon Kim, Ji Hyun Lee, Sohee Cho, Moon Young Kim, Soong Deok Lee, Eun Ho Ha, Jae Joon Ahn |
1Department of Applied Statistics, Yonsei University, Seoul, Korea.
2Department of Forensic Medicine, Seoul National University College of Medicine, Seoul, Korea.
3Institute of Forensic Science, Seoul National University College of Medicine, Seoul, Korea.
4Department of Information and Statistics, Yonsei University, Wonju, Korea. ahn2615@yonsei.ac.kr |
|
|
| Abstract |
|
In addition to identifying genetic differences between target populations, it is also important to determine the impact of genetic differences with regard to the respective target populations. In recent years, there has been an increasing number of cases where this approach is needed, and thus various statistical methods must be considered. In this study, genetic data from populations of Southeast and Southwest Asia were collected, and several statistical approaches were evaluated on the Y-chromosome short tandem repeat data. In order to develop a more accurate and practical classification model, we applied gradient boosting and ensemble techniques. To infer between the Southeast and Southwest Asian populations, the overall performance of the classification models was better than that of the decision trees and regression models used in the past. In conclusion, this study suggests that additional statistical approaches, such as data mining techniques, could provide more useful interpretations for forensic analyses. These trials are expected to be the basis for further studies extending from target regions to the entire continent of Asia as well as the use of additional genes such as mitochondrial genes. |
| Key Words:
Y-chromosomal short tandem repeats, Statistical models, Decision trees, Data mining, Ensemble model |
|
PDF Links
Full text via DOI
Download Citation
