Two new approaches to feature selection with harmony search

Ren Diao, Qiang Shen

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

18 Citations (SciVal)
174 Downloads (Pure)


Many search strategies have been exploited in implementing feature selection, in an effort to identify smaller and better subsets. Such work typically involves the use of heuristics in one form or another. In this paper two novel methods are presented by applying harmony search to feature selection. In particular, it demonstrates the potential of utilising this search mechanism in combination with fuzzy-rough feature evaluation. The resulting techniques are compared with approaches that rely on hill-climbing, genetic algorithms and particle swarm optimisation.
Original languageEnglish
Title of host publication2010 IEEE International Conference on Fuzzy Systems (FUZZ)
Number of pages7
Publication statusPublished - Jul 2010


Dive into the research topics of 'Two new approaches to feature selection with harmony search'. Together they form a unique fingerprint.

Cite this