The National Program on
Complex Data Structures


at the University of Toronto, Medical Science Building
August 14 -17, 2006 -- 9 AM to 5 PM

Director: Paul N Corey
Co-directors: Jamie Stafford and Wendy Lou
Lecture 6: DATA MINING -- Rafal Kustra

In the Data Mining lecture and subsequent Laboratory session, we will explore some of the modern Statistical approaches to Data Mining. The objective of the lecture will be to explain their workings in intuitive and graphical terms with only minimum required mathematics, and to highlight common features and important differences among them. Some methods we will consider are: tree models with an important Boosting extension, Neural Networks, and Support Vector Machines. In the laboratory session the participants will have an opportunity to apply some of these approaches to real dataset, and learn to draw proper conclusions from the results and modeling process.

Rafal Kustra is an Assistant Professor in Biostatistics at University of Toronto, and a Director of the Infornomics Lab for Statistical Genomics. His research focuses on Statistics and Data Mining Methods for high-dimensional data and his applied work has involved projects in silicon chip manufacturing, Neuroimaging and Bioinformatics. Prior to coming to University of Toronto, Dr Kustra was a co-founder and Chief Technology Officer of a Data Mining technology start-up in Silicon Valley.

Rafal Kustra, PhD
Assistant Professor, Biostatistics
Public Health Sciences, University of Toronto,
Health Sciences Building

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