Overview

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.

Full Product Details

Author:   Arnab Kumar Laha
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   Softcover reprint of the original 1st ed. 2019
Dimensions:   Width: 15.50cm , Height: 1.70cm , Length: 23.50cm
Weight:   0.480kg
ISBN:  

9789811345845

ISBN 10:   9811345848
Pages:   297
Publication Date:   10 January 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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

Reviews

Author Information

"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."

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