1. Clustering, performance evaluation, and Term Project 1.Term Project 2.Resource for review

2. Term Project Questions? Examples: –Research problems in Data MiningResearch problems in Data Mining –Industry problems in Data Mining/Data Warehousing –Explore new data with existing/new tools (C5, Cubist, Weka) –Explore data in comparative analysis (different algorithms, tool extensions, data selection, preprocessing ) –Focus on solving a problem (application or technical) and conduct a literature survey

3. Clustering (Dunham’s ppt Part II clustering 74-128) –Similarity and distance measures –Hierarchical algorithms (single link…) –Partition algorithms (K-Means, PAM,…)

4. Additional Notes on EM Algorithms: Clustering Witten’s book 218-224, pdf 94-104; –Background, introduction on Statistical based clustering (EM algorithm) Dunham’s book 47-51, Part I 52-54 –Basic concept of EM algorithm

5. Performance Evaluation Witten’s book Chapter 5 (see on-line notes)