Transparent Data Mining for Big and Small Data: 32 (Studies in Big Data) - Tapa blanda

Libro 20 de 95: Studies in Big Data
 
9783319852997: Transparent Data Mining for Big and Small Data: 32 (Studies in Big Data)
Tapa blanda
ISBN 10: 331985299X ISBN 13: 9783319852997
Editorial: Springer, 2018

Sinopsis

This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.
As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

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De la contraportada

This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.
As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2018
Idioma
Inglés
ISBN 10 
331985299X
ISBN 13 
9783319852997
Encuadernación
Tapa blanda
Número de páginas
236
Editor
Cerquitelli Tania, Quercia Daniele, Pasquale Frank
Contacto del fabricante
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

Europaplatz 3,69115 Heidelberg, Germany
Heidelberg
69115
Alemania

Otras ediciones populares con el mismo título

9783319540238: Transparent Data Mining for Big and Small Data: 32 (Studies in Big Data, 32)

Edición Destacada

ISBN 10:  3319540238 ISBN 13:  9783319540238
Editorial: Springer, 2017
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