Transparent Data Mining for Big and Small Data

Language: English

Published by Springer, 2018

331985299X / 9783319852997

Series: Book 20 of 95 - Studies in Big Data

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - 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.…

Seller Inventory # 9783319852997

Title
Transparent Data Mining for Big and Small Data
Author
Daniele Quercia
Publisher
Springer
Publication year
2018
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
331985299X
ISBN 13
9783319852997
Item weight
365 grams
Dimensions
235x155x13 mm
Series
Book 20 of 95: Studies in Big Data

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

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