Evolutionary Feature Selection
This thesis contains research on feature selection, in particular feature selection using evolutionary algorithms. Feature selection is motivated by increasing data-dimensionality and the need to construct simple induction models.
A literature review of evolutionary feature selection is conducted. After that a abstract feature selection algorithm, capable of using many different wrappers, is constructed. The algorithm is configured using a low-dimensional dataset. Finally it is tested on a wide range of datasets, revealing both it's abilities and problems.
The main contribution is the revelation that classifier accuracy is not a sufficient metric for feature selection on high-dimensional data.
Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2013. , 76 p.
IdentifiersURN: urn:nbn:no:ntnu:diva-24225Local ID: ntnudaim:8223OAI: oai:DiVA.org:ntnu-24225DiVA: diva2:702890
Kofod-Petersen, Anders, Førsteamanuensis II