Coefficient of Variation and Machine Learning Applications

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

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English

CRC Press
30 June 2021

Probability & statistics; Automatic control engineering; Computing: general

Series: Intelligent Signal Processing and Data Analysis

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.

By: K. Hima Bindu, Raghava Morusupalli, Nilanjan Dey, C. Raghavendra Rao
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 216mm, Width: 138mm,
Weight: 181g
ISBN: 9781032084190
ISBN 10: 1032084197
Series: Intelligent Signal Processing and Data Analysis
Pages: 148
Publication Date: 30 June 2021
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Paperback
Publisher's Status: Active

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.

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