Computer Science and High Dimensional Data Modelling

Abstract: The need to grasp large database structures is a very important issue in biological and life science. This review paper is aimed toward quantitative medical researchers searching for guidance in modeling large numbers of variables in medical research, how this relates to straightforward linear models and therefore the geometry that underlies their analysis. Issues reviewed include LASSO-related approaches, principal-component based analysis, and problems with model stability and interpretation. Model misspecification issues associated with potential nonlinearities are examined, as is that the Bayesian perspective on these issues.