We strive to deliver the best value to our customers and ensure complete satisfaction for all our textbook rentals.
You can return your online books for any reason within our refund period – no questions asked.
Every order is available for express shipping, and return shipping is always free.
You'll be happy with the quality of your books (or we'll ship you another one on our dime).
You can extend your rental up to 14 days – at the same cheap daily rental rate.
If you decide to keep the book it will never cost more than the purchase price.
As always, you have access to over 5 million titles. Plus, you can choose from 5 rental periods, so you only pay for what you’ll use. And if you ever run into trouble, our top-notch U.S. based Customer Service team is ready to help by email, chat or phone.
Supplemental materials are not guaranteed for used textbooks or rentals (access codes, DVDs, workbooks).
Statistical and Machine Learning Approaches for Network Analysis (Wiley Series in Computational Statistics)
by:Matthias Dehmer, Subhash C. Basak
Explore the multidisciplinary nature of complex networks through machine learning techniquesStatistical 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...
Explore the multidisciplinary nature of complex networks through machine learning techniquesStatistical 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 networksAn introduction to complex networks—measures, statistical properties, and modelsModeling for evolving biological networksThe structure of an evolving random bipartite graphDensity-based enumeration in structured dataHyponym extraction employing a weighted graph kernelStatistical 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.
Since launching the first textbook rental site in 2006, BookRenter has never wavered from our mission to make education more affordable for all students. Every day, we focus on delivering students the best prices, the most flexible options, and the best service on earth. On March 13, 2012 BookRenter.com, Inc. formally changed its name to Rafter, Inc. We are still the same company and the same people, only our corporate name has changed.