My current research area is classification based on ensembles of classifiers for
high-dimensional data. A robust classification procedure is developed based on ensembles
of classifiers, with each classifier constructed from a different set of predictors determined
by a random partition of the entire set of predictors. A primary area of application is the
classification of subjects into cancer-risk or cancer-type categories based on high-dimensional biomedical data. The methods can be used to improve class prediction in many
other areas of application involving high-dimensional prediction sets.
