Temporal Data Mining via Unsupervised Ensemble Learning (Paperback, UK ed.)

Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.

General

Imprint:	Elsevier Science Publishing Co Inc
Country of origin:	United States
Release date:	November 2016
First published:	2017
Authors:	Yun Yang
Dimensions:	235 x 191 x 9mm (L x W x T)
Format:	Paperback
Pages:	172
Edition:	UK ed.
ISBN-13:	978-0-12-811654-8
Categories:	Books > Computing & IT > Computer programming > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	0-12-811654-4
Barcode:	9780128116548

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