Advances in Analytics and Applications (Springer Proceedings in Business and Economics)
edited Arnab Kumar Laha
Advances in Analytics and Applications (Springer Proceedings in Business and Economics)
المؤلف
edited Arnab Kumar Lahaالناشر
Springerطبع 1
9783319770437
قائمة
شناسنامه
المدخل الرئيسي
Laha, Arnab Kumar، نویسندهالعنوان واسم المؤلف
Advances in Analytics and Applications (Springer Proceedings in Business and Economics) / edited Arnab Kumar Lahaبيانات النشر
: Springer، 2019مالمواصفات الشكلية
online resource (XI, 297 pages 64 illustrations).الموضوع
Big dataBusiness enterprises
Finance
Management
Big Data/Analytics
اللغة
انگلیسیالفهرس
کانورتورملاحظات
Part I: Overviews -- Chapter 1. Machine Learning -- Chapter 2. Regression Methods -- Chapter 3. Functional Data alysis -- 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 robability 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 arketing Campaign Success Rate Using Personalization -- et cetera.This book includes selected papers submitted to the CADABAI-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 analyticsapplications, machine learning applications, human resource analytics, operations analytics, analytics in finance, methodology and econometric applications. The papers in the predictive analytics applications section discuss webanalytics, 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 innovativeapplication 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. Description based on publisher-supplied MARC data..