Feature Selection Using Binary Cuckoo Search Algorithm

Kaya Y.

26th IEEE Signal Processing and Communications Applications Conference (SIU), İzmir, Turkey, 2 - 05 May 2018 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2018.8404843
  • City: İzmir
  • Country: Turkey
  • Karadeniz Technical University Affiliated: Yes

Abstract

The cuckoo search algorithm is one of the nature-inspired algorithms developed in recent years. Interesting breeding strategies of cuckoo birds have inspired the algorithm. The binary cuckoo search algorithm is a special version that reduces the search space to binary. In this study, we used binary cuckoo search algorithm in the feature selection process to classify the premature ventricular contraction beats in ECG. We used 200 amplitude values of the signal to represent one beat and selected those that represent the signal best. Using selected features, premature ventricular contraction beats were perceived with 99.67% of accuracy.