Advances in Analytics and Applications

Discusses innovative applications of analytics in business and introduces to new emerging areas of research in data analysis

Provides overviews on topics of current interest - machine learning, functional data analysis, regression analysis, directional data analysis and branching processes Academic research papers in analytics and business intelligence

Discusses innovative applications of analytics in business and introduces new emerging areas of research in data analysis Provides overviews on topics of current interestmachine learning, regression analysis, directional data analysis and branching processes Includes academic research papers that avoid complicated mathematical details and explain the concepts in a lucid manner

Auteur

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.

Contenu

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. <p