Machine Learning in Complex Networks by Thiago Christiano SilvaMachine Learning in Complex Networks by Thiago Christiano Silva

Machine Learning in Complex Networks

byThiago Christiano Silva, Liang Zhao

Hardcover | February 11, 2016

Pricing and Purchase Info

$182.83 online 
$220.95 list price save 17%
Earn 914 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks and network-based machine learning is presented, offering necessary background material. In the second part, we describe in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a stochastic particle competition technique for both non-supervised and semi-supervised learning using a stochastic nonlinear dynamical system is described in details. Moreover, an analytical analysis is supplied, which enables one to predict the behavior of the proposed technique. In addition, data reliability issues are explored in semi-supervised learning. Such matter has practical importance and is not often found in the literature. With the goal of validating these techniques for solving real problems, simulations on broadly accepted databases are conducted. Still in this book, we present a hybrid supervised classification technique that combines both low and high orders of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features, while the latter measures the compliance of the test instances with the pattern formation of the data. We show that the high level technique can realize classification according to the semantic meaning of the data. This book intends to combine two widely studied research areas, machine learning and complex networks, which in turn will generate broad interests to scientific community, mainly to computer science and engineering areas.
Title:Machine Learning in Complex NetworksFormat:HardcoverDimensions:331 pagesPublished:February 11, 2016Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319172891

ISBN - 13:9783319172897

Look for similar items by category:

Reviews

Table of Contents

Introduction.- Complex Networks.- Machine Learning.- Network Construction Techniques.- Network-Based Supervised Learning.- Network-Based Unsupervised Learning.- Network-Based Semi-Supervised Learning.- Case Study of Network-Based Supervised Learning: High-Level Data Classification.- Case Study of Network-Based Unsupervised Learning: Stochastic Competitive Learning in Networks.- Case Study of Network-Based Semi-Supervised Learning: Stochastic Competitive-Cooperative Learning in Networks.

Editorial Reviews

"The book explores the combined area of complex network-based machine learning. It presents the theoretical concepts underlying the two complementary parts as well as those related to their interaction with respect to supervised, unsupervised and semi-supervised learning. The latest developments in the field, together with real-world test scenarios, are additionally treated in detail." (Catalin Stoean, zbMATH 1357.68003, 2017)