Attribute value weighting in K-modes clustering for Y-short tandem repeats (Y-STR) surname
Ali Seman, Zainab Abu Bakar, Azizian Mohd Sapawi · 2010
This paper evaluates Y-STR Surname data for attribute value weighting in k-Modes clustering algorithm. Three categories weighting schemas: (1) Relative Value Frequency (RVF); (2) Uncommon Attribute Value Matches (UAVM); (3) Hybrid weighting schema are evaluated for Y-STR Surname data. The overall results show that the clustering accuracy of all methods produces in between 40-44% only. However, the idea of adapting a weighting schema still looks a promising method in order to improve the clustering accuracy for Y-STR data.