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.

�ber die Autorin bzw. den Autor

MATTHIAS DEHMER, PHD, is Head of the Institute for Bioinformatics and Trans- lational Research at the University for Health Sciences, Medical Informatics and Technology (Austria). He has written over 130 publications in his research areas, which include bioinformatics, systems biology, and applied discrete mathematics. Dr. Dehmer is also the coeditor of Applied Statistics for Network Biology, Statistical Modelling of Molecular Descriptors in QSAR/QSPR, Medical Biostatistics for Complex Diseases, Analysis of Complex Networks, and Analysis of Microarray Data, all published by Wiley.

SUBHASH C. BASAK, PHD, is Senior Research Associate at the Natural Resources Research Institute. He has published extensively in the areas of biochemical pharmacology, toxicology, mathematical chemistry, and computational chemistry.

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.

Anbieterinformationen

I mainly carry imported books from South East Asia / South Asia for readers of all Age Groups.

Zur Homepage des Verk�ufers

Unternehmensdaten des Verk�ufers

PLETOS INC
6931 51st Avenue, WOODSIDE, Woodside, NY, 11377, U.S.A.

Gesch�ftsbedingungen und Versandinformationen

Verkaufsbedingungen

We accept return for those books which are received damamged. Though we take appropriate care in packaing to avoid such situation.

Widerrufsbelehrung

Versandbedingungen

Versandkosten innerhalb von USA

Versandkosten innerhalb von USA
Bestellmenge	12 bis 19�Werktage	12 bis 14�Werktage
Erster Artikel	EUR 3.40	EUR 5.95

Die Versandzeiten werden von den Verk�uferinnen und Verk�ufern festgelegt. Sie variieren je nach Versanddienstleister und Standort. Sendungen, die den Zoll passieren, k�nnen Verz�gerungen unterliegen. Eventuell anfallende Abgaben oder Geb�hren sind von der K�uferin bzw. dem K�ufer zu tragen. Die Verk�uferin bzw. der Verk�ufer kann Sie bez�glich zus�tzlicher Versandkosten kontaktieren, um einen m�glichen Anstieg der Versandkosten f�r Ihre Artikel auszugleichen.