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Pattern recognition and big data
~
Pal, Amita.
Pattern recognition and big data
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Pattern recognition and big data[edited by] Amita Pal, Sankar K Pal.
其他作者:
Pal, Amita.
出版者:
Singapore :World Scientific,c2017.
面頁冊數:
1 online resource (875 p.) :ill. (some col.)
附註:
Title from PDF file title page (viewed February 3, 2017)
標題:
Big data.
電子資源:
http://www.worldscientific.com/worldscibooks/10.1142/10153#t=toc
ISBN:
9789813144552$q(electronic bk.)
Pattern recognition and big data
Pattern recognition and big data
[electronic resource] /[edited by] Amita Pal, Sankar K Pal. - 1st ed. - Singapore :World Scientific,c2017. - 1 online resource (875 p.) :ill. (some col.)
Title from PDF file title page (viewed February 3, 2017)
Includes bibliographical references and indexes.
"Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications. Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis."--Publisher's website.
Mode of access: World Wide Web.
ISBN: 9789813144552$q(electronic bk.)
LCCN: 2016025417Subjects--Topical Terms:
609582
Big data.
LC Class. No.: QA76.9.B45 / P35 2017
Dewey Class. No.: 005.7
Pattern recognition and big data
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http://www.worldscientific.com/worldscibooks/10.1142/10153#t=toc
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