Temporal Data Mining Unsupervised by Yang Yun (9 results)
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
£ 41.18
£ 10.00 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
Paperback. Condition: Brand New. 1st edition. 172 pages. 9.00x7.25x0.75 inches. In Stock.
- Softcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
Contact seller4-star sellerCondition: New
£ 46.52
£ 6.50 shippingShips from United Kingdom to U.S.A.Quantity: 3 available
Condition: New. pp. 172.
- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
Contact seller5-star sellerCondition: New
£ 37.66
£ 15.49 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Paperback. Condition: New.
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
Contact seller4-star sellerCondition: New
£ 56.33
£ 2.95 shippingShips within U.S.A.Quantity: 3 available
Condition: New. pp. 172.
- Softcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
Contact seller5-star sellerCondition: New
£ 47.73
£ 15.55 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
- Softcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
Contact seller4-star sellerCondition: New
£ 56.68
£ 8.55 shippingShips from Germany to U.S.A.Quantity: 3 available
Condition: New. pp. 172.
- Softcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
Contact seller5-star sellerCondition: New
£ 44.00
£ 4.73 shippingShips from Italy to U.S.A.Quantity: Over 20 available
Condition: new. Questo è un articolo print on demand.
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
Contact seller5-star sellerCondition: New
£ 45.09
£ 19.76 shippingShips from Germany to U.S.A.Quantity: 2 available
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 differ…ent 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. Englisch.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
£ 50.42
£ 26.20 shippingShips from Germany to U.S.A.Quantity: 2 available
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 p…erspectives. 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.
