Measurement of data complexity for classification problems with unbalanced data. (2nd May 2014)

• Record Type: Journal Article
• Authors: Anwar, Nafees; Jones, Geoff; Ganesh, Siva
• Is Part Of: Statistical analysis and data mining. Volume 7:Number 3(2014)
• Page Start: 194
• Page End: 211
• Publication Date: 2014-05-02
• Subjects: Data mining -- Statistical methods -- Periodicals; 006.312
• DOI: 10.1002/sam.11228
• Languages: English
• ISSNs: 1932-1864

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <p>We introduce a complexity measure for classification problems that takes account of deterioration in classifier performance as a result of class imbalance. The measure is based on <italic>k</italic>‐nearest neighbors. We explore the choices of <italic>k</italic> and the distance metric through a simulation study, and illustrate the use of our measure, and related data visualization techniques, with real datasets from the literature.</p> </abstract>