
Profit Driven Business Analytics
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Content
- Cover
- Title Page
- Copyright
- Contents
- Foreword
- Acknowledgments
- Chapter 1: A Value-Centric Perspective Towards Analytics
- Introduction
- Business Analytics
- Profit-Driven Business Analytics
- Analytics Process Model
- Analytical Model Evaluation
- Analytics Team
- Profiles
- Data Scientists
- Conclusion
- Review Questions
- Multiple Choice Questions
- Open Questions
- References
- Chapter 2: Analytical Techniques
- Introduction
- Data Preprocessing
- Denormalizing Data for Analysis
- Sampling
- Exploratory Analysis
- Missing Values
- Outlier Detection and Handling
- Principal Component Analysis
- Types of Analytics
- Predictive Analytics
- Introduction
- Linear Regression
- Logistic Regression
- Decision Trees
- Neural Networks
- Ensemble Methods
- Bagging
- Boosting
- Random Forests
- Evaluating Ensemble Methods
- Evaluating Predictive Models
- Splitting Up the Dataset
- Performance Measures for Classification Models
- Performance Measures for Regression Models
- Other Performance Measures for Predictive Analytical Models
- Descriptive Analytics
- Introduction
- Association Rules
- Sequence Rules
- Clustering
- Survival Analysis
- Introduction
- Survival Analysis Measurements
- Kaplan Meier Analysis
- Parametric Survival Analysis
- Proportional Hazards Regression
- Extensions of Survival Analysis Models
- Evaluating Survival Analysis Models
- Social Network Analytics
- Introduction
- Social Network Definitions
- Social Network Metrics
- Social Network Learning
- Relational Neighbor Classifier
- Probabilistic Relational Neighbor Classifier
- Relational Logistic Regression
- Collective Inferencing
- Conclusion
- Review Questions
- Multiple Choice Questions
- Open Questions
- Notes
- References
- Chapter 3: Business Applications
- Introduction
- Marketing Analytics
- Introduction
- RFM Analysis
- Response Modeling
- Churn Prediction
- X-selling
- Customer Segmentation
- Customer Lifetime Value
- Customer Journey
- Recommender Systems
- Fraud Analytics
- Credit Risk Analytics
- HR Analytics
- Conclusion
- Review Questions
- Multiple Choice Questions
- Open Questions
- Note
- References
- Chapter 4: Uplift Modeling
- Introduction
- The Case for Uplift Modeling: Response Modeling
- Effects of a Treatment
- Experimental Design, Data Collection, and Data Preprocessing
- Experimental Design
- Campaign Measurement of Model Effectiveness
- Uplift Modeling Methods
- Two-Model Approach
- Regression-Based Approaches
- Tree-Based Approaches
- Ensembles
- Continuous or Ordered Outcomes
- Evaluation of Uplift Models
- Visual Evaluation Approaches
- Performance Metrics
- Practical Guidelines
- Two-Step Approach for Developing Uplift Models
- Implementations and Software
- Conclusion
- Review Questions
- Multiple Choice Questions
- Open Questions
- Note
- References
- Chapter 5: Profit-Driven Analytical Techniques
- Introduction
- Profit-Driven Predictive Analytics
- The Case for Profit-Driven Predictive Analytics
- Cost Matrix
- Cost-Sensitive Decision Making with Cost-Insensitive Classification Models
- Cost-Sensitive Classification Framework
- Cost-Sensitive Classification
- Pre-Training Methods
- During-Training Methods
- Post-Training Methods
- Evaluation of Cost-Sensitive Classification Models
- Imbalanced Class Distribution
- Implementations
- Cost-Sensitive Regression
- The Case for Profit-Driven Regression
- Cost-Sensitive Learning for Regression
- During Training Methods
- Post-Training Methods
- Profit-Driven Descriptive Analytics
- Profit-Driven Segmentation
- Profit-Driven Association Rules
- Conclusion
- Review Questions
- Multiple Choice Questions
- Open Questions
- Notes
- References
- Chapter 6: Profit-Driven Model Evaluation and Implementation
- Introduction
- Profit-Driven Evaluation of Classification Models
- Average Misclassification Cost
- Cutoff Point Tuning
- ROC Curve-Based Measures
- Profit-Driven Evaluation with Observation-Dependent Costs
- Profit-Driven Evaluation of Regression Models
- Loss Functions and Error-Based Evaluation Measures
- REC Curve and Surface
- Conclusion
- Review Questions
- Multiple Choice Questions
- Open Questions
- Notes
- References
- Chapter 7: Economic Impact
- Introduction
- Economic Value of Big Data and Analytics
- Total Cost of Ownership (TCO)
- Return on Investment (ROI)
- Profit-Driven Business Analytics
- Key Economic Considerations
- In-Sourcing versus Outsourcing
- On Premise versus the Cloud
- Open-Source versus Commercial Software
- Improving the ROI of Big Data and Analytics
- New Sources of Data
- Data Quality
- Management Support
- Organizational Aspects
- Cross-Fertilization
- Conclusion
- Review Questions
- Multiple Choice Questions
- Open Questions
- Notes
- References
- About the Authors
- Index
- EULA
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