STAT597E/IST597E/CSE598E: Data Mining
Course Material

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Lecture notes

1. Introduction
2. Linear regression
3. Linear Methods for classification (regression of indicator matrix)
4. Linear discriminant analysis (I)
5. Linear discriminant analysis (II), Principal component analysis
6. Logistic regression
7. The perceptron learning algorithm
8. K-means (prototype method)
9. Clustering methods (K-center, dendrogram)
10. LVQ and k-nearest-neighbor
11. Classification and Regression Trees (I)
12. Classification and Regression Trees (II)
13. Mixture Model
14. Mixture discriminant analysis
15. Hidden Markov models

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Matlab Tips

See matlab tips at the this group.

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Projects

1. Project 1. Due on October 19, 2006.
2. Project 2. Due on November 14, 2006
3. Project 3. Due on November 30, 2006
4. Project 4. Due on December 14, 2006

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Data

• Aerial image classification
• Data sets taken from the UCI machine learning database repository :
  1. Sonar
  2. Ionosphere
  3. Glass
  4. Liver disorder
  5. Diabetes signs

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Jia Li

Last modified: Tue August 29 11:04:21 EDT 2006