ISBN: 9780471239291 - geometric data analysis: an empirical approach to dimensionality reduction and the study of patterns (22 resultados)

Condición: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: new.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. In English.

Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: New. This book addresses the most efficient methods of pattern analysis using wavelet decomposition. Readers will learn to analyze data in order to emphasize the differences between closely related patterns and then categorize them in a way that is useful to system users. Num Pages: 384 pages, illustrations. BIC Classification: PBKS; PBM; UYQP. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 243 x 166 x 26. Weight in Grams: 696. . 2000. 1st Edition. Hardcover. . . . .…

Gebunden. Condición: New. .provides a valuable summary of data reduction. (Technometrics, May 2002) .effectively describes and summarizes an emerging new field, namely, scientific data modeling and analysis. (Mathematical Reviews, 2003h)MICHAEL KIRBY is a professor in the.

Hardcover. Condición: Brand New. 1st edition. 361 pages. 9.50x6.00x1.00 inches. In Stock.

Condición: New. This book addresses the most efficient methods of pattern analysis using wavelet decomposition. Readers will learn to analyze data in order to emphasize the differences between closely related patterns and then categorize them in a way that is useful to system users. Num Pages: 384 pages, illustrations. BIC Classification: PBKS; PBM; UYQP. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 243 x 166 x 26. Weight in Grams: 696. . 2000. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Condición: New. pp. xvii + 363.

Condición: gut. 2001. Geometric Data Analysis: An Empirical Approach to Dimensionality Reduction and the Study of Patterns In englischer Sprache. pages.

Buch. Condición: Neu. Neuware - Unentbehrlich für die Praxis ist dieses Handbuch der Datenanalyse, das besonders auf die Unterschiede zwischen eng verwandten Patterns und auf deren zweckdienliche Kategorisierung eingeht. Zahlreiche Übungsaufgaben helfen beim Vertiefen der erarbeiteten theoretischen Konzepte.…

Condición: New. pp. xvii + 363 Illus. This item is printed on demand.

Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 726.

Hardcover. Condición: new. Hardcover. This book addresses the most efficient methods of pattern analysis using wavelet decomposition. Readers will learn to analyze data in order to emphasize the differences between closely related patterns and then categorize them in a way that is useful to system users. This book addresses the most efficient methods of pattern analysis using wavelet decomposition. Readers will learn to analyze data in order to emphasize the differences between closely related patterns and then categorize them in a way that is useful to system users. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condición: Brand New. 1st edition. 361 pages. 9.50x6.00x1.00 inches. In Stock. This item is printed on demand.

Condición: New. PRINT ON DEMAND pp. xvii + 363.