Advances in analytics and applications

Table of contents

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 describes an innovative application in the 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 part of the econometric application presents interesting banking and insurance applications.

https://www.springer.com/us/book/9789811312076