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IPMU
2010
Springer

Rank Correlation Coefficient Correction by Removing Worst Cases

8 years 8 months ago
Rank Correlation Coefficient Correction by Removing Worst Cases
Abstract. Rank correlation can be used to compare two linearly ordered rankings. If the rankings include noise values, the rank correlation coefficient will yield lower values than it actually should. In this paper, we propose an algorithm to remove pairs of values from rankings in order to increase Kendall's tau rank correlation coefficient. The problem itself is motivated from real data in bioinformatics context. Key words: Rank correlation coefficient, greedy algorithm, graph algorithms
Martin Krone, Frank Klawonn
Added 13 Feb 2011
Updated 13 Feb 2011
Type Journal
Year 2010
Where IPMU
Authors Martin Krone, Frank Klawonn
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