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fakenmc/amvidc

version 1.3.0.1 (120 KB) by Nuno Fachada
Clustering with minimum volume increase (MVI) and minimum direction change (MDC) clustering criteria

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Updated 27 Aug 2019

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AMVIDC is a data clustering algorithm based on agglomerative hierarchical clustering (AHC) which uses minimum volume increase (MVI) and minimum direction change (MDC) as clustering criteria.

The algorithm is described in detail in the following publication:

Fachada, N., Figueiredo, M.A.T., Lopes, V.V., Martins, R.C., Rosa, A.C., Spectrometric differentiation of yeast strains using minimum volume increase and minimum direction change clustering criteria, Pattern Recognition Letters, vol. 45, pp. 55-61 (2014), doi: http://dx.doi.org/10.1016/j.patrec.2014.03.008

Code and user manual also available at GitHub: https://github.com/fakenmc/amvidc

Cite As

Fachada, N., Figueiredo, M.A.T., Lopes, V.V., Martins, R.C., Rosa, A.C., Spectrometric differentiation of yeast strains using minimum volume increase and minimum direction change clustering criteria, Pattern Recognition Letters, vol. 45, pp. 55-61 (2014), doi: http://dx.doi.org/10.1016/j.patrec.2014.03.008

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MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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