Supervised and Unsupervised Learning for Data Science (Hardcover, 1st ed. 2020)

This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018). Includes new advances in clustering and classification using semi-supervised and unsupervised learning; Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning; Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Unsupervised and Semi-Supervised Learning
Release date:	September 2019
First published:	2020
Editors:	Michael W. Berry • Azlinah Mohamed • Bee Wah Yap
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	187
Edition:	1st ed. 2020
ISBN-13:	978-3-03-022474-5
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-03-022474-0
Barcode:	9783030224745

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