Graph-Based Clustering and Data Visualization Algorithms

by Ágnes Vathy-Fogarassy, János Abonyi

Overview

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.

Product Details

ISBN-13:	9781447151586
Publisher:	Springer-Verlag New York, LLC
Publication date:	05/24/2013
Series:	SpringerBriefs in Computer Science
Sold by:	Barnes & Noble
Format:	eBook
Pages:	110
File size:	3 MB

About the Author

L. Santiago Medina, MD, MPH, is Co-Director, Division of Neuroradiology-Neuroimaging, and Director, Health Outcomes, Policy, and Economics (HOPE) Center at Miami Children's Hospital.
Jeffrey G. Jarvik, MD, MPH,is the Professor of Radiology and Neurological Surgery, Adjunct Associate Professor of Health Services, and Director of Radiology Health Service Research Section at the University of Washington School of Medicine.
Pina C. Sanelli, MD, MPH,is Associate Professor of Radiology and is also Associate Professor of Public Health at Weill Cornell Medical College. She is an Associate Attending Radiologist at the NewYork-Presbyterian Hospital-Weill Cornell Campus. Dr. Sanelli is a member of the Division of Neuroradiology. Her clinical expertise is in neuroradiological and spine imaging and procedures including MRI, MRA, CT, and CTA.

Table of Contents

Vector Quantisation and Topology-Based Graph Representation.- Graph-Based Clustering Algorithms.- Graph-Based Visualisation of High-Dimensional Data.