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      Book

      Coefficient of Variation and Machine Learning Applications
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      Book

      Coefficient of Variation and Machine Learning Applications

      DOI link for Coefficient of Variation and Machine Learning Applications

      Coefficient of Variation and Machine Learning Applications book

      Coefficient of Variation and Machine Learning Applications

      DOI link for Coefficient of Variation and Machine Learning Applications

      Coefficient of Variation and Machine Learning Applications book

      ByK. Hima Bindu, M Raghava, Nilanjan Dey, C. Raghavendra Rao
      Edition 1st Edition
      First Published 2019
      eBook Published 9 December 2019
      Pub. Location Boca Raton
      Imprint CRC Press
      DOI https://doi.org/10.1201/9780429296185
      Pages 148
      eBook ISBN 9780429296185
      Subjects Computer Science, Engineering & Technology, Mathematics & Statistics
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      Get Citation

      Bindu, K.H., Raghava, M., Dey, N., & Rao, C.R. (2019). Coefficient of Variation and Machine Learning Applications (1st ed.). CRC Press. https://doi.org/10.1201/9780429296185

      ABSTRACT

      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.

      TABLE OF CONTENTS

      chapter Chapter 1|26 pages

      Introduction to Coefficient of Variation

      chapter Chapter 2|15 pages

      CV Computational Strategies

      chapter Chapter 3|14 pages

      Image Representation

      chapter Chapter 4|22 pages

      Supervised Learning

      chapter Chapter 5|10 pages

      Applications

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