9780470722107 - graphical models: representations for learning, reasoning and data mining: 704 (wiley series in computational statistics) de borgelt, christian; steinbrecher, matthias; kruse, rudolf r. (12 resultados)

- Tapa dura
Librería: INDOO, Avenel, NJ, Estados Unidos de AmericaINDOO
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 112,82
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.

- Tapa dura
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 110,46
Envío por EUR 2,31Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.

- Tapa dura
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 128,44
Envío por EUR 2,31Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: As New. Unread book in perfect condition.

- Tapa dura
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 148,90
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Graphical models are of increasing importance in applied statistics, and in particular in data mining. Providing a self-contained introduction and overview to learning relational, probabilistic, and possibilistic networks from data, this second edition of Graphical Models is thoroughly updat…ed to include the latest research in this burgeoning field, including a new chapter on visualization. The text provides graduate students, and researchers with all the necessary background material, including modelling under uncertainty, decomposition of distributions, graphical representation of distributions, and applications relating to graphical models and problems for further research. Provides a self-contained introduction to learning relational, probabilistic and possibilistic networks from data All basic concepts carefully explained and illustrated by examples throughout Contains background material including graphical representation, including Markov and Bayesian Networks. Includes a comprehensive bibliography. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 135,98
Envío por EUR 17,41Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.

Graphical Models: Representations for Learning, Reasoning and Data Mining (Wiley Series in Computational Statistics)
Borgelt, Christian; Steinbrecher, Matthias; Kruse, Rudolf R.
- Tapa dura
Librería: Ubiquity Trade, Miami, FL, Estados Unidos de AmericaUbiquity Trade
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 164,35
Envío por EUR 2,63Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Brand new! Please provide a physical shipping address.

- Tapa dura
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 160,02
Envío por EUR 10,50Se envía de Irlanda a Estados Unidos de AmericaCantidad disponible: 15 disponibles
Condición: New. Provides a self-contained introduction to learning relational, probabilistic and possibilistic networks from data All basic concepts carefully explained and illustrated by examples throughout Contains background material including graphical representation, including Markov and Bayesian Networks. Includes a compre…hensive bibliography. Series: Wiley Series in Computational Statistics. Num Pages: 404 pages, Illustrations. BIC Classification: PBT; TJ; UNF. Category: (P) Professional & Vocational. Dimension: 240 x 160 x 27. Weight in Grams: 718. . 2009. 2nd Revised edition. Hardcover. . . . .

- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 162,00
Envío por EUR 17,41Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.

- Tapa dura
Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 150,06
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Gebunden. Condición: New. The use of graphical models in applied statistics has increased considerably in recent years. At the same time the field of data mining has developed as a response to the large amounts of available data. This book addresses the overlap between these two imp.

- Tapa dura
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 162,01
Envío por EUR 42,96Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Graphical models are of increasing importance in applied statistics, and in particular in data mining. Providing a self-contained introduction and overview to learning relational, probabilistic, and possibilistic networks from data, this second edition of Graphical Models is thoroughly updat…ed to include the latest research in this burgeoning field, including a new chapter on visualization. The text provides graduate students, and researchers with all the necessary background material, including modelling under uncertainty, decomposition of distributions, graphical representation of distributions, and applications relating to graphical models and problems for further research. Provides a self-contained introduction to learning relational, probabilistic and possibilistic networks from data All basic concepts carefully explained and illustrated by examples throughout Contains background material including graphical representation, including Markov and Bayesian Networks. Includes a comprehensive bibliography. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

- Tapa dura
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 204,13
Envío por EUR 9,20Se envía dentro de Estados Unidos de AmericaCantidad disponible: 15 disponibles
Condición: New. Provides a self-contained introduction to learning relational, probabilistic and possibilistic networks from data All basic concepts carefully explained and illustrated by examples throughout Contains background material including graphical representation, including Markov and Bayesian Networks. Includes a compre…hensive bibliography. Series: Wiley Series in Computational Statistics. Num Pages: 404 pages, Illustrations. BIC Classification: PBT; TJ; UNF. Category: (P) Professional & Vocational. Dimension: 240 x 160 x 27. Weight in Grams: 718. . 2009. 2nd Revised edition. Hardcover. . . . . Books ship from the US and Ireland.

- Tapa dura
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 231,54
Envío por EUR 32,42Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Graphical models are of increasing importance in applied statistics, and in particular in data mining. Providing a self-contained introduction and overview to learning relational, probabilistic, and possibilistic networks from data, this second edition of Graphical Models is thoroughly updat…ed to include the latest research in this burgeoning field, including a new chapter on visualization. The text provides graduate students, and researchers with all the necessary background material, including modelling under uncertainty, decomposition of distributions, graphical representation of distributions, and applications relating to graphical models and problems for further research. Provides a self-contained introduction to learning relational, probabilistic and possibilistic networks from data All basic concepts carefully explained and illustrated by examples throughout Contains background material including graphical representation, including Markov and Bayesian Networks. Includes a comprehensive bibliography. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.