Feature Selection Based on Relaxed Linear Separability
Leon Bobrowski, Tomasz Łukaszuk · 2009
Feature selection problem appears where large number of features constraint effective data analysis and processing. Identification of the most important feature subsets is a crucial challenge in many important applications. For example, a basic question in bioinformatics which is identification of genes functionalities, can be formulated and answered as a problem of this kind. Identification of the most important feature subsets through minimisation of convex and piecewise-linear (CPL) criterion function is described and analysed in the paper. This approach is combined with relaxation of the linear separability assumption. K e y w o r d s: feature selection, relaxed linear separability, CPL criterion function 1.