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Transparent Data Mining for Big and Small Data

-15% su kodu: ENG15
201,57 
Įprasta kaina: 237,14 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
201,57 
Įprasta kaina: 237,14 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 237.1400 InStock
Nemokamas pristatymas į paštomatus per 11-15 darbo dienų užsakymams nuo 20,00 

Knygos aprašymas

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.

Informacija

Serija: Studies in Big Data
Leidėjas: Springer Nature Switzerland
Išleidimo metai: 2017
Knygos puslapių skaičius: 236
ISBN-10: 3319540238
ISBN-13: 9783319540238
Formatas: 241 x 160 x 19 mm. Knyga kietu viršeliu
Kalba: Anglų

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