Abstract: This paper reports on the experimental results of the k-modes-type algorithms for partitioning Y-Short Tandem Repeats (Y-STR) data. The results were based on the clustering accuracy scores of five hard and three soft k-modes-type algorithms. Six Y-Short Tandem Repeats data sets were used as a benchmark for the evaluation. The results clearly indicated that the soft k-modes-type clustering algorithms are the most reliable algorithms for partitioning Y-STR data.