Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
This paper presents Centre-based hard clustering approaches for clustering Y-STR data. Two classical partitioning techniques: Centroid-based partitioning technique and Representative object-based partitioning technique are evaluated. The k-Means and the k-Modes algorithms are the fundamental algorit...
Kaydedildi:
| Asıl Yazarlar: | , , |
|---|---|
| Materyal Türü: | Kitap |
| Baskı/Yayın Bilgisi: |
Faculty of Computer and Mathematical Sciences,
2010.
|
| Konular: | |
| Online Erişim: | Link Metadata |
| Etiketler: |
Etiketle
Etiket eklenmemiş, İlk siz ekleyin!
|
| Özet: | This paper presents Centre-based hard clustering approaches for clustering Y-STR data. Two classical partitioning techniques: Centroid-based partitioning technique and Representative object-based partitioning technique are evaluated. The k-Means and the k-Modes algorithms are the fundamental algorithms for the centroid-based partitioning technique, whereas the k-Medoids is a representative object-based partitioning technique. The three algorithms above are experimented and evaluated in partitioning Y-STR haplogroups and Y-STR Surname data. The overall results show that the centroid-based partitioning technique is better than the representative object-based partitioning technique in clustering Y-STR data. |
|---|---|
| Diğer Bilgileri: | https://ir.uitm.edu.my/id/eprint/11101/1/11101.pdf |