Statistical and Machine Learning Approaches for Network Analysis is popular PDF and ePub book, written by Matthias Dehmer in 2012-06-26, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Statistical and Machine Learning Approaches for Network Analysis can be Read Online from any device for your convenience.
Statistical and Machine Learning Approaches for Network Analysis Book PDF Summary
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.
Detail Book of Statistical and Machine Learning Approaches for Network Analysis PDF
- Author : Matthias Dehmer
- Release : 26 June 2012
- Publisher : John Wiley & Sons
- ISBN : 9781118346983
- Genre : Mathematics
- Total Page : 269 pages
- Language : English
- PDF File Size : 15,9 Mb
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