Generating Sample Points in General Metric Space

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 486)

Abstract

The importance of general metric spaces in modeling of complex objects is increasing. A key aspect in testing of algorithms on general metric spaces is the generation of appropriate sample set of objects. The chapter demonstrates that the usual way, i.e. the mapping of elements of some vector space into general metric space is not an optimal solution. The presented approach maps the object set into the space of distance-matrixes and proposes a random walk sample generation method to provide a better uniform distribution of test elements.

Keywords

General metric space Sample generation Distance cone 

Notes

Acknowledgments

This research was carried out as part of the TAMOP-4.2.1.B-10/2/KONV-2010-0001 project with support by the European Union, co-financed by the European Social Fund and the technical background was supported by the Hungarian National Scientific Research Fund Grant OTKA K77809.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Information TechnologyUniversity of MiskolcMiskolcHungary

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