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Coefficient of Variation and Machine Learning Applications
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Coefficient of Variation and Machine Learning Applications

Book Details

Format Hardback or Cased Book
ISBN-10 0367273284
ISBN-13 9780367273286
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 2nd, 2019
Print length 148 Pages
Weight 306 grams
Dimensions 14.40 x 22.30 x 1.50 cms
Ksh 10,800.00
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This book explains computational strategies, properties of Coefficient of Variation (CV) and related metadata extraction. It includes representational/classification strategies through illustrative explanations. CV in context of contemporary Machine Learning strategies and Big Data paradigms is explained through selected applications.

Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies, properties of CV and extracting the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV through illustrative explanations. The potential nature of CV in the context of contemporary Machine Learning strategies and the Big Data paradigms is demonstrated through selected applications. Overall, this book explains statistical parameters and knowledge representation models.


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