Dehmer Matthias (EN) — Statistical and Machine Learning Approaches for Network Analysis

Тут можно читать онлайн книгу Dehmer Matthias (EN) - Statistical and Machine Learning Approaches for Network Analysis - бесплатно полную версию (целиком). Жанр книги: Иностранная литература. Вы можете прочесть полную версию (весь текст) онлайн без регистрации и смс на сайте Lib-King.Ru (Либ-Кинг) или прочитать краткое содержание, аннотацию (предисловие), описание и ознакомиться с отзывами (комментариями) о произведении.

Statistical and Machine Learning Approaches for Network Analysis
Язык книги: Английский
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Statistical and Machine Learning Approaches for Network Analysis краткое содержание

Statistical and Machine Learning Approaches for Network Analysis - описание и краткое содержание, автор Dehmer Matthias (EN), читать бесплатно онлайн на сайте электронной библиотеки Lib-King.Ru.

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.

Statistical and Machine Learning Approaches for Network Analysis - читать онлайн бесплатно полную версию (весь текст целиком)

Statistical and Machine Learning Approaches for Network Analysis - читать книгу онлайн бесплатно, автор Dehmer Matthias (EN)

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