InstanceRank: Bringing order to datasets

Authors:
Carlos G. Vallejo;José A. Troyano;F. Javier Ortega
Affiliations:
Department of Computer Languages and Systems, University of Seville, Avda. Reina, Mercedes s/n, 41012 Seville, Spain;Department of Computer Languages and Systems, University of Seville, Avda. Reina, Mercedes s/n, 41012 Seville, Spain;Department of Computer Languages and Systems, University of Seville, Avda. Reina, Mercedes s/n, 41012 Seville, Spain
Venue:
Pattern Recognition Letters
Year:
2010

Citing 16
Cited 2

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Abstract

In this paper we present InstanceRank, a ranking algorithm that reflects the relevance of the instances within a dataset. InstanceRank applies a similar solution to that used by PageRank, the web pages ranking algorithm in the Google search engine. We also present ISR, an instance selection technique that uses InstanceRank. This algorithm chooses the most representative instances from a learning database. Experiments show that ISR algorithm, with InstanceRank as ranking criteria, obtains similar results in accuracy to other instance reduction techniques, noticeably reducing the size of the instance set.