Title: Using Support Vector Machines to Classify Microarray Data
Director(s): Louise A. Raphael, Daniel A. Williams, Department of Mathematics
Dates of Program: May 23 - July 1, 2005
Summary: In the first part of the REU, the Howard University students will classify DNA microarray data by K-means clustering and principal component analysis (PCA) using MATLAB. They will write a MATLAB program for K-means and develop the theory for PCA.
In the second part of the REU, basic concepts of support vector machines (SVM) will be presented and the DNA microarray data used in the first part will be classified using SVM. Classification results will be compared with those obtained by K-means and PCA.
- Michelle Burke, Washington, DC
- Lester Duruewuru, Washington, DC
- Jonathan Watkins, Alexandria, VA
- Kendall Williams, Dallas, TX
- Soumaila Diarra, Silver Spring, MD
- Ron Rogers, Trinidad, West Indies
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