Graph-Based Clustering and Data Visualization Algorithms

Nonfiction, Science & Nature, Mathematics, Graphic Methods, Computers, Database Management, General Computing
Cover of the book Graph-Based Clustering and Data Visualization Algorithms by Ágnes Vathy-Fogarassy, János Abonyi, Springer London
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Ágnes Vathy-Fogarassy, János Abonyi ISBN: 9781447151586
Publisher: Springer London Publication: May 24, 2013
Imprint: Springer Language: English
Author: Ágnes Vathy-Fogarassy, János Abonyi
ISBN: 9781447151586
Publisher: Springer London
Publication: May 24, 2013
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer London

Cover of the book Computational Intelligence by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Self-* and P2P for Network Management by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Methodologies for Developing and Managing Emerging Technology Based Information Systems by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Simulation Training in Laparoscopy and Robotic Surgery by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Astronomy with Small Telescopes by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Stereo Scene Flow for 3D Motion Analysis by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Formal Methods: State of the Art and New Directions by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Plastic Surgery by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Neurocritical Care by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Pathology of the Pancreas by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Transanal Stapling Techniques for Anorectal Prolapse by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Aspiration Cytology in the Staging of Urological Cancer by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Pediatric and Congenital Cardiac Care by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Germ Cell Tumours V by Ágnes Vathy-Fogarassy, János Abonyi
Cover of the book Reinventing Ourselves: Contemporary Concepts of Identity in Virtual Worlds by Ágnes Vathy-Fogarassy, János Abonyi
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy