Graph-Based Clustering and Data Visualization Algorithms by Ágnes Vathy-Fogarassy,János Abonyi

By Ágnes Vathy-Fogarassy,János Abonyi

This paintings offers a knowledge visualization procedure that mixes graph-based topology illustration and dimensionality aid how you can visualize the intrinsic information constitution in a low-dimensional vector house. the appliance of graphs in clustering and visualization has a number of merits. A graph of vital edges (where edges represent kin and weights characterize similarities or distances) offers a compact illustration of the total complicated info set. this article describes clustering and visualization tools which are in a position to make the most of details hidden in those graphs, in accordance with the synergistic mixture of clustering, graph-theory, neural networks, info visualization, dimensionality aid, fuzzy tools, and topology studying. The paintings comprises various examples to assist within the figuring out and implementation of the proposed algorithms, supported through a MATLAB toolbox on hand at an linked website.

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