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Graph-Based Clustering and Data Visualization Algorithms

Name: Graph-Based Clustering and Data Visualization Algorithms
Brand: Springer, Berlin
SKU: 9781447151579
Price: 330.7 RON
Availability: InStock

Autor: Ágnes Vathy-Fogarassy, János Abonyi

Limbă:

Legare: Carte broșată

Editura: Springer, Berlin

Disponibilitate: În depozitul extern

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This work presents a data visualization technique that combines graph-based topology representation...

Informații despre carte

Autor

Ágnes Vathy-Fogarassy, János Abonyi

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2013

Pagini

110

EAN

9781447151579

ISBN

1447151577

Enbook ID

01426231

Editura

Springer, Berlin

Greutate

454

Dimensiuni

156 x 8 x 236

Descriere completă

This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on the synergistic combination of clustering, graph-theory, neural networks, data visualization, dimensionality reduction, fuzzy methods, and topology learning. The work contains numerous examples to aid in the understanding and implementation of the proposed algorithms, supported by a MATLAB toolbox available at an associated website.