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Coefficient of Variation and Machine Learning Applications: Intelligent Signal Processing and Data Analysis

Autor K. Hima Bindu, Raghava Morusupalli, Nilanjan Dey, C. Raghavendra Rao
en Limba Engleză Paperback – 30 iun 2021
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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Specificații

ISBN-13: 9781032084190
ISBN-10: 1032084197
Pagini: 148
Ilustrații: 30 Illustrations, black and white
Dimensiuni: 138 x 216 x 8 mm
Greutate: 0.18 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Intelligent Signal Processing and Data Analysis


Cuprins

1. Introduction to Statistical Dispersion 2. Coefficient of Variation 3. Coefficient of Variation Computational Strategies 4. Coefficient of Variation Based Image Representation 5. Coefficient of Variation based Decision Tree (CvDT) 6. Some Applications.

Notă biografică

K. Hima Bindu, Raghava Morusupalli, Nilanjan Dey, C. Raghavendra Rao

Descriere

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.