This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests (TM), neural nets, support vector machines, nearest neighbors and boosting.

N� de ref. del art�culo 0103749

Contactar al vendedor

Denunciar este art�culo

Detalles bibliogr�ficos

T�tulo

Statistical Learning for Biomedical Data

Editor

Cambridge University Press

Fecha de publicaci�n

2011

Idioma

Ingl�s

ISBN 10

0521699096

ISBN 13

9780521699099

Encuadernaci�n

Paperback

Estado

Very Good

Cat�logos de vendedores

Acerca de

Sinopsis

This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests™, neural nets, support vector machines, nearest neighbors and boosting.

Acerca de los autores

James D. Malley is a Research Mathematical Statistician in the Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, at the National Institutes of Health.

Karen G. Malley is president of Malley Research Programming, Inc. in Rockville, Maryland, providing statistical programming services to the pharmaceutical industry and the National Institutes of Health. She also serves on the global council of the Clinical Data Interchange Standards Consortium (CDISC) user network, and the steering committee of the Washington, DC area CDISC user network.

Sinisa Pajevic is a Staff Scientist in the Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, at the National Institutes of Health.

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

Descripci�n de la librer�a

Oxfordshire UK booksellers of many years standing.

Ver la p�gina web de la librer�a

Informaci�n empresarial del vendedor

Bill & Ben Books ltd
Manor Cottage, Great Coxwell, Faringdon, SN7 7NB, United Kingdom

Condiciones de venta y env�o

Condiciones de venta

Bill & Ben Books Ltd

All books are shipped in New or Used condition as described in the listing. We post promptly, orders usually ship within 1-2 business days. We are happy to accept returns up to 30 days from purchase. Domestic Shipments are sent by Royal Mail, and International by Airmail. Please contact us directly if you wish to return an order. Name of business :

Derecho a cancelaci�n

Condiciones de env�o

Orders usually ship within 1-2 business days. Domestic Shipments are sent by Royal Mail, and International by Airmail. We are happy to accept returns upto 30 days from purchase. Please contact us directly if you wish to return an order

Tarifas de env�o de Reino Unido a Espa�a

Tarifas de env�o de Reino Unido a Espa�a
Cantidad del pedido	De 25 a 45 d�as h�biles	De 8 a 14 d�as h�biles
Primer art�culo	EUR 11.69	EUR 21.81

Los plazos de entrega los establecen los vendedores y var�an seg�n el transportista y la ubicaci�n. Los pedidos que pasan por la aduana pueden sufrir retrasos y los compradores son responsables de los aranceles o tarifas asociadas. Los vendedores pueden ponerse en contacto con usted en relaci�n con cargos adicionales para cubrir cualquier aumento en los costes de env�o de los art�culos.

Informaci�n detallada sobre el vendedor