Coefficient of variation and machine learning applications
著者
書誌事項
Coefficient of variation and machine learning applications
(CRC focus)
CRC Press, c2020
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注記
Other authors: Raghava Morusupalli, Nilanjan Dey, C. Raghavendra Rao
Includes bibliographical references (p. 121-123) and index
内容説明・目次
内容説明
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.
目次
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.
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