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ECOM 6349 Selected Topics in Artificial Intelligence: Cluster Analysis
Instructor: Wesam Ashour
Office: B231
Email: [email protected]
Course Webpage:
Text Book:
Guojun Gan, Chaoqun Ma, and Jianhong Wu. Data Clustering: Theory,
Algorithms, and Applications.
Data Clustering, Data Types, Scale Conversion, Data Standardization and
Transformation, Similarity and Dissimilarity Measures, Hierarchical Clustering
Techniques, Fuzzy Clustering Algorithms, Center Based Clustering Algorithms,
Graph Based Clustering Algorithms, Grid Based Clustering Algorithms, Density
Based Clustering Algorithms, Model Based Clustering Algorithms, Evaluation of
Clustering Algorithms.
We will cover as much as we can!
Chapter 8 and 9: Introduction to Data Mining by Pang-Ning Tan, Michael
Steinbach, and Vipin Kumar
Skills required:
Any programming Language: C\C++, Java, or Matlab
Grades: 1- 20% Assignment.
2- 40% Final Exam.
3- 40% Original Scientific Paper.
Important Dates:
Assignment dates: Will be organized later!
Paper Initial Submession: Saturday, 7th May 2011
Paper (last version) submession: Wednesday 25th May 2011
Final Exam: Saturday, 28th May 2011, 14:00-17:00, K107
Important Advice:
From first day in the semester you should work very hard and you must activate your
mind to think as much as you can!