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Analysis of k-partite ranking algorithm in area under the receiver operating characteristic curve criterion.
- Source :
-
International Journal of Computer Mathematics . Aug2018, Vol. 95 Issue 8, p1527-1547. 21p. - Publication Year :
- 2018
-
Abstract
- The k-partite ranking, as an extension of bipartite ranking, is widely used in information retrieval and other computer applications. Such implement aims to obtain an optimal ranking function which assigns a score to each instance. The AUC (Area Under the ROC Curve) measure is a criterion which can be used to judge the superiority of the given k-partite ranking function. In this paper, we study the k-partite ranking algorithm in AUC criterion from a theoretical perspective. The generalization bounds for the k-partite ranking algorithm are presented, and the deviation bounds for a ranking function chosen from a finite function class are also considered. The uniform convergence bound is expressed in terms of a new set of combinatorial parameters which we define specially for the k-partite ranking setting. Finally, the generally margin-based bound for k-partite ranking algorithm is derived. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00207160
- Volume :
- 95
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- International Journal of Computer Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 129755006
- Full Text :
- https://doi.org/10.1080/00207160.2017.1322688