Graph-based clustering and data visualization algorithms

Combines graph-based topology representation and dimensionality reduction methods
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Aggiornato 10 lug 2014

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This Matlab package is written specifically for the book Ágnes Vathy-Fogarassy and János Abonyi: Graph-based clustering and data visualization algorithms (http://www.abonyilab.com/books/gclustbook). The purpose of the package is to demonstrate a wide range of graph-based clustering and visualization algorithms presented in the book. The package contains graph-based algorithms for vector quantization (e.g. kmeans, Neural Gas method, Topology Representing Networks, etc.), for clustering (e.g. Hybrid Minimal Spanning Tree - Gath-Geva algorithm, improved Jarvis-Patrick algorithm, etc.) and for low-dimensional visualization of high-dimensonal data set (e.g. Isomap, Curvilinear Component Analysis, Topology Representing Network Map - TRNMap, etc.)

For more details and other MATLAB tools for graph analaysis please visit:
http://www.abonyilab.com/books/gclustbook

Cita come

Janos Abonyi (2024). Graph-based clustering and data visualization algorithms (https://www.mathworks.com/matlabcentral/fileexchange/47196-graph-based-clustering-and-data-visualization-algorithms), MATLAB Central File Exchange. Recuperato .

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Creato con R14SP1
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Versione Pubblicato Note della release
1.0.0.0