a greedy clustering algorithm based on interval pattern concepts and the problem of optimal box positioning

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2017
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Abstract
We consider a clustering approach based on interval pattern concepts. Exact algorithms developed within the framework of this approach are unable to produce a solution for high-dimensional data in a reasonable time, so we propose a fast greedy algorithm which solves the problem in geometrical reformulation and shows a good rate of convergence and adequate accuracy for experimental high-dimensional data. Particularly, the algorithm provided high-quality clustering of tactile frames registered by Medical Tactile Endosurgical Complex.
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nersisyan2017journala Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Stepan A. Nersisyan;Vera V. Pankratieva;Vladimir M. Staroverov;Vladimir E. Podolskii
Journal Chemico-biological interactions
Year 2017
DOI
10.1155/2017/4323590
URL
http://dx.doi.org/10.1155/2017/4323590
Keywords
mathematics

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