Output details

Feature subset selection in large dimensionality domains

<13> Feature subset selection (dimensionality reduction) is critical for big data applications. The algorithm proposed here is an efficient compromise which has both good convergence characteristics (and is tested on both repository and novel datasets) and the capability for very effective operation on large datasets. Recent research has followed this path, both in producing new techniques and in applications (for example, see R.Fandos, Signal Processing, November, 2013; M.B.Imani et al, Applied Artificial Intelligence, 27(5), 2013).