Coefficient of Variation and Machine Learning Applications, K. Hima Bindu,M Raghava,Nilanjan Dey,C. Raghavendra Rao (9781032084190) — Readings Books

Become a Readings Member to make your shopping experience even easier. Sign in or sign up for free!

Become a Readings Member. Sign in or sign up for free!

Hello Readings Member! Go to the member centre to view your orders, change your details, or view your lists, or sign out.

Hello Readings Member! Go to the member centre or sign out.

Coefficient of Variation and Machine Learning Applications
Paperback

Coefficient of Variation and Machine Learning Applications

$58.99
Sign in or become a Readings Member to add this title to your wishlist.

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.

Read More
In Shop
Out of stock
Shipping & Delivery

$9.00 standard shipping within Australia
FREE standard shipping within Australia for orders over $100.00
Express & International shipping calculated at checkout

MORE INFO
Format
Paperback
Publisher
Taylor & Francis Ltd
Country
United Kingdom
Date
30 June 2021
Pages
148
ISBN
9781032084190

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.

Read More
Format
Paperback
Publisher
Taylor & Francis Ltd
Country
United Kingdom
Date
30 June 2021
Pages
148
ISBN
9781032084190