Genetic Algorithm for the Column Subset Selection Problem

The column subset selection problem is a well-known hard optimization problem of selecting an optimal subset of k columns from the matrix A^m×n, k<; n, so that the cost function is minimized. The problem is of practical importance for data mining and processing since it can be used for unsupervised feature selection, dimension reduction, and many other applications. This work proposes a new genetic algorithm for the column subset selection problem and evaluates it in a series of computational experiments.