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Transparent Data Mining for Big and Small Data
. Ed(S): Cerquitelli, Tania; Quercia, Daniele; Pasquale, Frank
€ 183.35
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Description for Transparent Data Mining for Big and Small Data
Hardback. Editor(s): Cerquitelli, Tania; Quercia, Daniele; Pasquale, Frank. Series: Studies in Big Data. Num Pages: 210 pages, 5 black & white illustrations, 17 colour illustrations, 17 colour tables, biography. BIC Classification: GPFC; KJQ; LN; UGK; UMB. Category: (P) Professional & Vocational. Dimension: 235 x 155. .
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 ... Read more
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 ... Read more
Product Details
Format
Hardback
Publication date
2017
Publisher
Springer International Publishing AG Switzerland
Number of pages
210
Condition
New
Series
Studies in Big Data
Number of Pages
215
Place of Publication
Cham, Switzerland
ISBN
9783319540238
SKU
V9783319540238
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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