1. Introduction
2. Data Preprocessing
3. Mining Frequent Patterns, Association, and Correlation
4. Classification and Prediction
   • Decision Tree
   • Bayesian Classification
     • Naive Bayesian Classification
     • Bayesian Belief Networks
   • Rule-Based Classification
   • Neural Network
   • Support  Vector Machines
   • Associative Classification
   • Lazy Learners
     • k-Nearest-Neighbor Classifiers
   • Genetic Algorithm
5. Cluster Analysis