Statistical and Machine Learning Approaches for Network Analysis (Hardcover, New)

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: * A survey of computational approaches to reconstruct and partition biological networks * An introduction to complex networks measures, statistical properties, and models * Modeling for evolving biological networks * The structure of an evolving random bipartite graph * Density-based enumeration in structured data * Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.

General

Imprint:	John Wiley & Sons
Country of origin:	United States
Release date:	September 2012
First published:	2012
Authors:	M Dehmer
Dimensions:	239 x 163 x 23mm (L x W x T)
Format:	Hardcover
Pages:	344
Edition:	New
ISBN-13:	978-0-470-19515-4
Categories:	Books > Science & Mathematics > Mathematics > Combinatorics & graph theory Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	0-470-19515-0
Barcode:	9780470195154

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