Machine Learning

Text Book

Data Mining: Practical Machine Learning Tools and Techniques (2nd Edition), 天瓏代理

Ian H. Witten & Eibe Frank. Morgan Kaufmann, June 2005, ISBN 0-12-088407-0

http://www.cs.waikato.ac.nz/ml/weka/book.html

The Weka machine learning workbench.

Reference Book
- Introduction to Machine Learning, by Ethem Alpaydin The MIT Press (October 1, 2004) ISBN: 0262012111
- Bioinformatics : The Machine Learning Approach, 2nd Edition. The MIT Press (2001) ISBN: 026202506X
- Machine Learning, Tom Mitchell, McGraw-Hill (March 1, 1997) ISBN: 0070428077
- Data Mining : A Tutorial-based Primer, Addison Wesley, 2003, ISBN : 0-201-74128-8
- Text Mining Application Programming, Thomson, Manu Konchady, 2006, ISBN: 1-58450-460-9
Grading
- Project (50%):
  - Decision Tree
    - Examples:
    - Please design a classifier using decision tree via Weka.
      - key points
        
        Feature selection (filter)
        
        Converting discrete to numeric attributes.
        
        Accuracy comparison according to different decision trees.
  - Mining Association Rules
    - Using the package Apriori in Weka. to mining for association rules.
  - Make a report described what you have observed.
  - Make a discussion based on your experiments.
  - Project Plan Date : 2007.4.11
  - Presentation Date : 2007.4.18
  - Report Date : 2007.4.25
- Project (25%): Linear Classifier
  - DNA Sequence Classification
  - Presentation Date : 2007.5.23
  - Report Date : 2007.5.30
- Project (25%): Support Vector Machine
  - DNA_sequence_classification(by SVM)
    - compare the previous experimental results with linear classifier.
  - Presentation Date : 2007.6.20
  - Report Date : 2007.6.27