Evaluation of k-modes-type algorithms for clustering Y-short tandem repeats data
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 benchm...
| Published in: | Trends in Bioinformatics |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Asian Network for Scientific Information
2012
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861419270&doi=10.3923%2ftb.2012.47.52%c2%a0&partnerID=40&md5=0d7697b86d0b15a1c8fd691b0acc83d8 |
| Summary: | 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. © 2012 Asian Network for Scientific Information. |
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| ISSN: | 19947941 |
| DOI: | 10.3923/tb.2012.47.52 |