Contour approximation of data: A duality theory

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Date

2009-05-01

Author

İyigün, Cem
Ben-Israel, Adi

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Given a dataset D partitioned in clusters, the joint distance function (JDF)J(x) at any point x is the harmonic mean of the distances between x and the cluster centers. The JDF is a continuous function, capturing the data points in its lower level sets (a property called contour approximation), and is a useful concept in probabilistic clustering and data analysis.

Subject Keywords

Geometry and Topology, Algebra and Number Theory, Numerical Analysis, Discrete Mathematics and Combinatorics

URI

https://hdl.handle.net/11511/48395

Journal

LINEAR ALGEBRA AND ITS APPLICATIONS

DOI

https://doi.org/10.1016/j.laa.2009.01.023

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Department of Industrial Engineering, Article

Citation Formats

C. İyigün and A. Ben-Israel, “Contour approximation of data: A duality theory,” LINEAR ALGEBRA AND ITS APPLICATIONS, vol. 430, no. 10, pp. 2771–2780, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48395.