Download Database Management Systems (COSC 340H)

yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Cluster analysis wikipedia , lookup

Nonlinear dimensionality reduction wikipedia , lookup

K-means clustering wikipedia , lookup

Trent University
Department of Computer Science/Studies
Data Mining (AMOD 501H)
Sabine McConnell ([email protected])
Department of Computer Science/Studies
OC 102.7
748-1011 ext. 7803
Course Description:
An introduction to the principles of data mining. Topics to be covered include an
overview of existing work in data mining with a special focus on applications in
astronomy, sampling mechanisms, the statistical foundations of data mining, the problem
of missing data, and outlier detection. We will discuss classification techniques such as
Support Vector Machines, Neural Networks, and Decision Trees, as well as clustering
techniques including k-means, self-organizing maps, and the Expectation Maximization
algorithm. Furthermore, the course includes a practical component using open source
Assigned readings will consist of chapters from the book ‘Introduction to Data Mining’
by Tan, Steinbach, and Kumar (Addison-Wesley, 2006), supplemented by relevant
journal publications and conference proceedings.