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Advances in Analytics and Applications

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advances in Analytics and Applications/ edited by Arnab Kumar Laha.
其他作者:	Laha, Arnab Kumar.
面頁冊數:	XI, 297 p. 64 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Big data. -
電子資源:	https://doi.org/10.1007/978-981-13-1208-3
ISBN:	9789811312083

Advances in Analytics and Applications
Advances in Analytics and Applications[electronic resource] /edited by Arnab Kumar Laha. - 1st ed. 2019. - XI, 297 p. 64 illus.online resource. - Springer Proceedings in Business and Economics,2198-7246. - Springer Proceedings in Business and Economics,.

Part I: Overviews -- Chapter 1. Machine Learning -- Chapter 2. Regression Methods -- Chapter 3. Functional Data Analysis -- Chapter 4. Directional Data Analysis -- Chapter 5.Branching Processes -- Part II: Predictive Analysis Applications -- Chapter 6. Click-Through Rate Estimation using CHAID Classification Tree Model -- Chapter 7 . Predicting Success Probability in Professional Tennis Tournaments: Using a Logistic Regression Model -- Chapter 8. Hausdorff Path Clustering and Hidden Markov Model Applied to Person Movement Prediction in Retail Spaces -- Chapter 9. Improving Email Marketing Campaign Success Rate Using Personalization -- etc.

This book includes selected papers submitted to the ICADABAI-2017 conference, offering an overview of the new methodologies and presenting innovative applications that are of interest to both academicians and practitioners working in the area of analytics. It discusses predictive analytics applications, machine learning applications, human resource analytics, operations analytics, analytics in finance, methodology and econometric applications. The papers in the predictive analytics applications section discuss web analytics, email marketing, customer churn prediction, retail analytics and sports analytics. The section on machine learning applications then examines healthcare analytics, insurance analytics and machine analytics using different innovative machine learning techniques. Human resource analytics addresses important issues relating to talent acquisition and employability using analytics, while a paper in the section on operations analytics describe an innovative application in oil and gas industry. The papers in the analytics in finance part discuss the use of analytical tools in banking and commodity markets, and lastly the econometric applications part presents interesting banking and insurance applications.

ISBN: 9789811312083

Standard No.: 10.1007/978-981-13-1208-3doiSubjects--Topical Terms:

981821
Big data.

LC Class. No.: HF5548.125-5548.6

Dewey Class. No.: 658.4038

Advances in Analytics and Applications
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