Advances in Analytics and Applications

ISBN-13: 9789811312076 / Angielski / Twarda / 2018 / 297 str.

Arnab Kumar Laha

Opis

It discusses predictive analytics applications, machine learning applications, human resource analytics, operations analytics, analytics in finance, methodology and econometric applications.

Spis treści

PART I:  Overviews

1.       Machine Learning

2.       Regression Methods

3.       Functional Data Analysis

4.       Directional Data Analysis

5.       Branching Processes

PART II: PREDICTIVE ANALYTICS APPLICATIONS

6.       Click-Through Rate Estimation using CHAID Classification Tree Model

7.       Predicting Success Probability in Professional Tennis Tournaments: Using a Logistic Regression Model

8.       Hausdorff Path Clustering and Hidden Markov Model Applied to Person Movement Prediction in Retail Spaces

9.       Improving Email Marketing Campaign Success Rate Using Personalization

10.   Predicting Customer Churn for DTH: Building Churn Score Card for DTH

11.   Applying Predictive Analytics in a Continuous Process Industry

PART III: MACHINE LEARNING APPLICATIONS

12.   Automatic Detection of Tuberculosis using Deep Learning Methods

13.   Connected Cars and Driving Pattern: An Analytical Approach to Risk Based Insurance

14.    Hybrid Machine Learning and Cognitive approach using Telematics and IoT for Tackling Downtime of Commercial Vehicles and Taxis

PART IV: HUMAN RESOURCE ANALYTICS

15.   Analytics-led Talent Acquisition for Improving Efficiency and Effectiveness

16.   Assessing Student Employability to Help Recruiters Find the Right Candidates

 PART V : OPERATIONS ANALYTICS

17.   Innovative          Heuristics            Modeling             for          Dynamic               Project                 Cost Optimization

18.   Estimation of Fluid Flow Rate and Mixture Composition using Low Cost Acoustic Sensors for Application in the Oil and Gas Industry

PART VI: ANALYTICS IN FINANCE

19.   Loan Loss Provisioning Practices in Indian Banks

20.   Modeling Leptokurtic Return Distributions in Commodity Markets

PART VII : METHODOLOGY

21.   OLS: Is That So Useless for Regression with Categorical Data?

22.   Estimation of Parameters of Misclassified Size Biased Borel

23.   A Stochastic Feedback Queuing Model with Encouraged Arrivals and Retention of Impatient Customers

PART VIII: ECONOMETRIC APPLICATIONS

24.   Does Banking Competition Granger Cause Banking Stability: The Study of SEM Countries

25.   The Relationship Between Insurance and Economic Growth in India: A Cross-region Study Using an Econometric Approach

O autorze

Prof. Arnab K Laha takes keen interest in understanding how analytics, machine learning and artificial intelligence can be leveraged to solve complex problems of business and society.  His areas of research and teaching interest include Advanced Data Analytics, Quality Management and Risk Modeling.  He has published papers in national and international journals of repute in these areas and has served on the editorial board of several journals including Statistical Analysis and Data Mining: The ASA Data Science Journal. He was featured among India’s best business school professors by Business Today in 2006 and Business India in 2012 and was named as one of the “10 Most Prominent Analytics Academicians in India” by Analytics India Magazine in 2014 and 2017. He is the convener of the biennial IIMA series of conferences on Advanced Data Analysis, Business Analytics and Intelligence. He is the author of the popular book on analytics entitled "How to Make the Right Decision" published by Penguin-Random House.  He has conducted large number of training programmes and undertaken consultancy work in the fields of business analytics, quality management and risk management.

Blurb

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.