In this research, we investigated a new algorithm called FSALPS (Feature Selection Age Layered Population Structure) evolutionary algorithm. We adapted the ALPS algorithm with all its inherent benefits with some other innovative evolutionary strategies to produce an algorithm that performs feature selection and classification without converging on a local optima
“ALPS is able to overcome the problem of premature convergence in stochastic algorithms.”Greg Hornby ALPS Researcher
FSALPS performs effective feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies.