General

We experiment with two types of clustering, K-medians and a dimension-reduction technique known as Approximate Distance Clustering, for classifying lung adenocarcinomas into high-risk and low-risk groups according to gene expression values from microarray data. We base this classification on a reduced set of genes obtained by Nearest Shrunken Mean [4] or a combination of a vraince-based approach with hierarchical clustering