1. Introduction
   • ppt1
2. Data Preprocessing
   • Text Processing: Perl
   • Database: MySQL
   • Web Server:
   • jdwang_PerlPractice
   • ppt2
3. Mining Frequent Patterns, Association, and Correlation
   • Chapter 5. Mining Frequent Patterns, Associations and Correlations
   • ppt3
4. Classification and Prediction
   • ppt5
   • Decision Tree Learning
     • 002~chapter_4_DT.ppt
     • i2ml-chap9-v1-1_DT_jdwang.ppt
     • 002~chapter_6_Classifier_DT.ppt
   • Bayesian Decision Theory
     • Naive Bayes Classifier (From Tom M. Mitchell)
     • i2ml-chap3-v1-1_NB_jdwang.ppt
     • Naive_Bayes_training_example_Tennis.htm
       • Naive_Bayes_training_example_Tennis_ans.htm

• Support Vector Machine (SVM)
  • SVM
  • DNA Sequence Classification Practice (by SVM)
  • CS583-supervised-learning
  • Chapter 6. Classification and Prediction

5. Cluster Analysis
   • Chapter 7. Cluster Analysis
6. Dimensional Reduction
   • Clustering
   • Attribute Selection
   • Feature Selection
7. Mining Time-Series Data.ppt
8. Mining Sequence Patterns in Biological Databases
9. Mining Text and Web Data
10. ApplicationsandTrendsinDataMining.ppt