Transparent Data Mining for Big and Small Data
Softcover reprint of the original 1st ed. 2017
Book Details
Format
Paperback / Softback
Book Series
Studies in Big Data
ISBN-10
331985299X
ISBN-13
9783319852997
Edition
Softcover reprint of the original 1st ed. 2017
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jul 28th, 2018
Print length
215 Pages
Product Classification:
Cybernetics & systems theoryCybernetics and systems theoryEntertainment & media lawEntertainment and media lawMaths for engineersAlgorithms & data structuresAlgorithms and data structuresDatabasesDatabases / Data managementData miningComputer modelling & simulationComputer modelling and simulationExpert systems / knowledge-based systems
Ksh 21,600.00
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This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions.
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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