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Coefficient of Variation and Machine Learning Applications K. Hima Bindu

Coefficient of Variation and Machine Learning Applications By K. Hima Bindu

Coefficient of Variation and Machine Learning Applications by K. Hima Bindu


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Summary

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 and Machine Learning Applications Summary

Coefficient of Variation and Machine Learning Applications by K. Hima Bindu

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.

About K. Hima Bindu

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

Table of Contents

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.

Additional information

NLS9781032084190
9781032084190
1032084197
Coefficient of Variation and Machine Learning Applications by K. Hima Bindu
New
Paperback
Taylor & Francis Ltd
2021-06-30
148
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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