Coefficient of Variation and Machine Learning Applications [electronic resource].
Material type:
TextSeries: Publisher: Milton : CRC Press LLC, 2019Description: 1 online resource (149 p.)ISBN: 9781000752229; 1000752224; 9780429296185; 0429296185; 9781000752427; 1000752429; 9781000752625; 1000752623Subject(s): COMPUTERS / Machine Theory | COMPUTERS / Computer Engineering | MATHEMATICS / Probability & Statistics / General | Analysis of variance | Big data -- Statistical methodsDDC classification: 519.538 | 510 LOC classification: QA76.95Online resources: Taylor & Francis | OCLC metadata license agreement Summary: 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.
Description based upon print version of record.
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.
OCLC-licensed vendor bibliographic record.