| 书目名称 | Machine Learning in Complex Networks | | 编辑 | Thiago Christiano Silva,Liang Zhao | | 视频video | | | 概述 | This book combines two important and popular research areas: complex networks and machine learning.This book contains not only fundamental background, but also recent research results.Numerous illustr | | 图书封面 |  | | 描述 | 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 thisbook, 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 | | 出版日期 | Book 2016 | | 关键词 | Community Detection; Complex Networks; Data Classification; Data Clustering; Machine Learning | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-17290-3 | | isbn_softcover | 978-3-319-79234-7 | | isbn_ebook | 978-3-319-17290-3 | | copyright | Springer International Publishing Switzerland 2016 |
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发表于 2025-3-21 17:35:19
