HASTIE, TREVOR; TIBSHIRANI, ROBERT; FRIEDMAN, JEROME (25 Ergebnisse)

Hardcover. Zustand: Good. Second Edition 2009. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.

gebundene Ausgabe. Zustand: Gut. 532 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 1105.

Zustand: Good. Used book that is in clean, average condition without any missing pages.

Hardcover. Zustand: Very Good. Second Edition 2009. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.

Soft cover. Zustand: New. Zustand des Schutzumschlags: New. International Edition. **INTERNATIONAL EDITION** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments go through via USPS/UPS/DHL with tracking numbers. Great professional textbook selling experience and expedite shipping service.

Zustand: New. In.

Gebunden. Zustand: New. The many topics include neural networks, support vector machines, classification trees and boosting - the first comprehensive treatment of this topic in any book Includes over 200 pages of four-color graphicsThe many topics include neur.

Zustand: good. A good reading copy. May contain markings or be a withdrawn library copy.

Hardcover. Zustand: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.

Hardcover. Zustand: Poor. No Jacket. First Edition. Hardcover edition in Poor condition. 5th printing. The bottom center of the covers are show heavy wear exposing the boards. Corners are bumped. Spine ends crushed. The binding is in good shape but the book is slightly rolled backwards. Small abrasion to the front flyleaf. The interior pages are heavily creased at the front edge. Feel free to contact me for pictures. The book will be carefully packaged for shipment for protection from the elements. USPS electronic tracking number issued free of charge.

Zustand: Acceptable. Fairly worn, but readable and intact. If applicable: Dust jacket, disc or access code may not be included.

Zustand: New. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.

Hardcover. Zustand: New. ISBN:9780387848570.

Zustand: Good. There is handwriting, stickers or numbers inside the front cover Cover/Case has some rubbing and edgewear. Access codes, CDs, slipcovers and other accessories may not be included.

Zustand: New. Well packaged and promptly shipped from California. US veteran operated.

Zustand: New.

hardcover. Zustand: LikeNew. Pages are New and Unused, Front or Back cover is damaged- torn, wrinkled or dented., Used Like New, no missing pages, no damage to binding, may have a remainder mark.

Hardback. Zustand: New. Second Edition 2009. This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression and path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates.

Hardback. Zustand: New. Second Edition 2009. This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression and path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates.

Hardcover. Zustand: Like New. Like New. book.

Hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

hardcover. Zustand: Very Good. A clean, cared for item that is unmarked and shows limited shelf wear.

Hardback. Zustand: New. Second Edition 2009. This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression and path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates.

Zustand: Good. This item is in overall good condition. Covers and dust jackets are intact but may have minor wear including slight curls or bends to corners as well as cosmetic blemishes including stickers. Pages are intact but may have minor highlighting/ writing. Binding is intact; however, spine may have slight wear overall. Digital codes may not be included and have not been tested to be redeemable and/or active. Minor shelf wear overall. Please note that all items are donated goods and are in used condition. Orders shipped Monday through Friday! Your purchase helps put people to work and learn life skills to reach their full potential. Orders shipped Monday through Friday. Your purchase helps put people to work and learn life skills to reach their full potential. Thank you!

Hardcover. Zustand: New. This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for "wide'' data (p bigger than n), including multiple testing and false discovery rates.