Lecture Notes

• Course Introduction (pdf, video)
• Data Mining (pdf, video)
• Machine Learning for Data Mining (pdf, video)
• Data Representation (pdf, video)
• Association Rules
• Basics (pdf, video)
• Advanced Topics (pdf, video)
• Clustering
• Introduction (pdf, video)
• Partitioning Clustering (pdf, video)
• Hierarchical Clustering (pdf, video)
• Density-based, grid-based, and model-based clustering (pdf, video)
• Classification
• Introduction (pdf, video)
• Decision Trees (pdf, video1, video2)
• Rules (pdf, video)
• Naive Bayes & IBL (pdf, video)
• Evaluation (pdf, video)
• Ensemble Methods: Bagging, Boosting and Random Forests (pdf)
• Mining Data Streams (pdf)

Software

• Rapid Miner (homepage, download)

Exams

• Spring 2007 (zip)
• Spring 2008 (zip)
• Spring 2009 (zip)