Analytics in a Big Data World · the Essential Guide to Data Science and Its Applications by Baesens, Bart -- Read -- Imperial Library of Trantor

Index

Preface Acknowledgments Chapter 1 Big Data and Analytics

Example Applications Basic Nomenclature Analytics Process Model Job Profiles Involved Analytics Analytical Model Requirements Notes

Chapter 2 Data Collection, Sampling, and Preprocessing

Types of Data Sources Sampling Types of Data Elements Visual Data Exploration and Exploratory Statistical Analysis Missing Values Outlier Detection and Treatment Standardizing Data Categorization Weights of Evidence Coding Variable Selection Segmentation Notes

Chapter 3 Predictive Analytics

Target Definition Linear Regression Logistic Regression Decision Trees Neural Networks Support Vector Machines Ensemble Methods Multiclass Classification Techniques Evaluating Predictive Models Notes

Chapter 4 Descriptive Analytics

Association Rules Sequence Rules Segmentation Notes

Chapter 5 Survival Analysis

Survival Analysis Measurements Kaplan Meier Analysis Parametric Survival Analysis Proportional Hazards Regression Extensions of Survival Analysis Models Evaluating Survival Analysis Models Notes

Chapter 6 Social Network Analytics

Social Network Definitions Social Network Metrics Social Network Learning Relational Neighbor Classifier Probabilistic Relational Neighbor Classifier Relational Logistic Regression Collective Inferencing Egonets Bigraphs Notes

Chapter 7 Analytics: Putting It All to Work

Backtesting Analytical Models Benchmarking Data Quality Software Privacy Model Design and Documentation Corporate Governance Notes

Chapter 8 Example Applications

Credit Risk Modeling Fraud Detection Net Lift Response Modeling Churn Prediction Recommender Systems Web Analytics Social Media Analytics Business Process Analytics Notes

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