Temporal Data Mining via Unsupervised Ensemble Learning

0 avg rating
( 0 ratings by Goodreads )
 
9780128116548: Temporal Data Mining via Unsupervised Ensemble Learning

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.

  • Includes fundamental concepts and knowledge, covering all key tasks and techniques of temporal data mining, i.e., temporal data representations, similarity measure, and mining tasks
  • Concentrates on temporal data clustering tasks from different perspectives, including major algorithms from clustering algorithms and ensemble learning approaches
  • Presents a rich blend of theory and practice, addressing seminal research ideas and looking at the technology from a practical point-of-view

"synopsis" may belong to another edition of this title.

From the Back Cover:

Temporal Data Mining via Unsupervised Ensemble Learning not only provides an overview of temporal data mining and an in-depth knowledge of temporal data clustering and ensemble learning techniques but also provides a rich blend of theory and practice with three proposed novel approaches.
Since each temporal clustering approach favors differently structured temporal data or types of temporal data with certain assumptions, and since there is nothing universal that can solve all problems, this book enables practitioners to understand the characteristics of both clustering algorithms and the target temporal data so as to select the right approach to successfully solve each different situation.
Key Features
· The first novel approach is based on the ensemble of Hidden Markov Model-based partitioning clustering, associated with a hierarchical clustering refi nement, to solve problems by finding the intrinsic number of clusters and model initialization problems which exist in most model-based clustering algorithms
· The second approach presents an unsupervised ensemble learning model of iteratively constructed partitions on a sub-training set obtained by a hybrid sampling scheme which provides a potential solution for large temporal data clustering tasks
· The third proposed approach is a feature-based approach to temporal data clustering, through a weighted ensemble of a simple clustering algorithm with minimum user-dependent parameters, to address both proper grouping with minimum computational cost and provide a generic technique for the optimal solution of combining multiple partitions
Temporal Data Mining via Unsupervised Ensemble Learning not only enumerates the existing techniques proposed so far, but also classifi es and organizes them in a way that is of help for a practitioner looking for solutions to a concrete problem. The evidence suggests that ensemble learning techniques may give an optimal solution for dealing with temporal data clustering problems, and this book presents the case in an accessible format designed to appeal to both students and professional researchers, including those with little mathematical and statistical background.

About the Author:

Dr Yang has a very solid and broad knowledge and experience in computer science, and in-depth expertise in machine learning, data mining and temporal data processing. His main research area is in the temporal data mining and unsupervised ensemble learning. In these topics, he has produced some internationally excellent research results including proposing and developing several innovation methods and algorithms. These works have been published in the international leading research journals or conferences such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Systems, Man, and Cybernetics- Part C, and Knowledge-Based Systems. His research results have attracted a lot of attentions from the machine learning research community and made the significant impact. As an evidence to illustrate the attention that his work has received and the impact his work has produced, his IEEE Transaction publication “Temporal data clustering via weighted clustering ensemble with different representations has been cited more than 42 times based on Google scholar.

"About this title" may belong to another edition of this title.

Buy New View Book
List Price: US$ 69.95
US$ 51.38

Convert Currency

Shipping: FREE
From United Kingdom to U.S.A.

Destination, Rates & Speeds

Add to Basket

Top Search Results from the AbeBooks Marketplace

1.

Yun Yang
Published by Elsevier Science Publishing Co Inc, United States (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Paperback Quantity Available: 1
Seller:
The Book Depository
(London, United Kingdom)
Rating
[?]

Book Description Elsevier Science Publishing Co Inc, United States, 2016. Paperback. Book Condition: New. UK ed.. Language: English . Brand New Book. 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. Bookseller Inventory # AA59780128116548

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 51.38
Convert Currency

Add to Basket

Shipping: FREE
From United Kingdom to U.S.A.
Destination, Rates & Speeds

2.

Yun Yang
Published by Elsevier Science Publishing Co Inc, United States (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Paperback Quantity Available: 1
Seller:
The Book Depository US
(London, United Kingdom)
Rating
[?]

Book Description Elsevier Science Publishing Co Inc, United States, 2016. Paperback. Book Condition: New. UK ed.. Language: English . Brand New Book. 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. Bookseller Inventory # AA59780128116548

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 56.35
Convert Currency

Add to Basket

Shipping: FREE
From United Kingdom to U.S.A.
Destination, Rates & Speeds

3.

Yun Yang
Published by Elsevier 2016-12-01 (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Paperback Quantity Available: 3
Seller:
Chiron Media
(Wallingford, United Kingdom)
Rating
[?]

Book Description Elsevier 2016-12-01, 2016. Paperback. Book Condition: New. Bookseller Inventory # NU-GRD-05507271

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 55.25
Convert Currency

Add to Basket

Shipping: US$ 3.94
From United Kingdom to U.S.A.
Destination, Rates & Speeds

4.

Yang, Yun
Published by Elsevier (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Quantity Available: 3
Seller:
Books2Anywhere
(Fairford, GLOS, United Kingdom)
Rating
[?]

Book Description Elsevier, 2016. PAP. Book Condition: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Bookseller Inventory # GB-9780128116548

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 50.32
Convert Currency

Add to Basket

Shipping: US$ 11.87
From United Kingdom to U.S.A.
Destination, Rates & Speeds

5.

Yang, Yun
Published by Elsevier Science Ltd (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Paperback Quantity Available: 2
Seller:
Revaluation Books
(Exeter, United Kingdom)
Rating
[?]

Book Description Elsevier Science Ltd, 2016. Paperback. Book Condition: Brand New. 1st edition. 172 pages. 9.00x7.25x0.75 inches. In Stock. Bookseller Inventory # __0128116544

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 55.97
Convert Currency

Add to Basket

Shipping: US$ 7.92
From United Kingdom to U.S.A.
Destination, Rates & Speeds

6.

Yang, Yun
Published by Elsevier (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Softcover First Edition Quantity Available: 3
Rating
[?]

Book Description Elsevier, 2016. Book Condition: New. Num Pages: 172 pages, illustrations. BIC Classification: UMT; UNF; UYQ. Category: (P) Professional & Vocational. Dimension: 196 x 276 x 13. Weight in Grams: 378. . 2016. 1st Edition. Paperback. . . . . . Bookseller Inventory # V9780128116548

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 68.51
Convert Currency

Add to Basket

Shipping: FREE
From Ireland to U.S.A.
Destination, Rates & Speeds

7.

YANG, YUN
Published by Elsevier (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Paperback Quantity Available: 1
Seller:
Herb Tandree Philosophy Books
(Stroud, GLOS, United Kingdom)
Rating
[?]

Book Description Elsevier, 2016. Paperback. Book Condition: NEW. 9780128116548 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Bookseller Inventory # HTANDREE01208872

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 58.43
Convert Currency

Add to Basket

Shipping: US$ 10.55
From United Kingdom to U.S.A.
Destination, Rates & Speeds

8.

Yun Yang
Published by Elsevier (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Softcover Quantity Available: 3
Seller:
Ria Christie Collections
(Uxbridge, United Kingdom)
Rating
[?]

Book Description Elsevier, 2016. Book Condition: New. book. Bookseller Inventory # ria9780128116548_rkm

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 64.05
Convert Currency

Add to Basket

Shipping: US$ 5.11
From United Kingdom to U.S.A.
Destination, Rates & Speeds

9.

Yang, Yun
Published by Elsevier
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Softcover Quantity Available: 3
Seller:
Kennys Bookstore
(Olney, MD, U.S.A.)
Rating
[?]

Book Description Elsevier. Book Condition: New. Num Pages: 172 pages, illustrations. BIC Classification: UMT; UNF; UYQ. Category: (P) Professional & Vocational. Dimension: 196 x 276 x 13. Weight in Grams: 378. . 2016. 1st Edition. Paperback. . . . . Books ship from the US and Ireland. Bookseller Inventory # V9780128116548

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 70.11
Convert Currency

Add to Basket

Shipping: FREE
Within U.S.A.
Destination, Rates & Speeds

10.

Yang, Yun
Published by Elsevier (2016)
ISBN 10: 0128116544 ISBN 13: 9780128116548
New Quantity Available: > 20
Print on Demand
Seller:
Books2Anywhere
(Fairford, GLOS, United Kingdom)
Rating
[?]

Book Description Elsevier, 2016. PAP. Book Condition: New. New Book. Delivered from our UK warehouse in 3 to 5 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bookseller Inventory # LQ-9780128116548

More Information About This Seller | Ask Bookseller a Question

Buy New
US$ 59.63
Convert Currency

Add to Basket

Shipping: US$ 11.89
From United Kingdom to U.S.A.
Destination, Rates & Speeds

There are more copies of this book

View all search results for this book