Paper Info
Title
Feature selection using binary cuckoo search algorithm.
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.
Year
Venue
Keywords
2018
Signal Processing and Communications Applications Conference
Cuckoo search algorithm,Levy Flight,ECG,feature selection,arrhythmia classification,k-NN,Neural Networks
Field
DocType
ISSN
Pattern recognition,Feature selection,Computer science,Cuckoo,Algorithm,Cuckoo search,Feature extraction,Artificial intelligence,Statistical classification,Signal processing algorithms,Binary number
Conference
2165-0608
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Kaya, Yasin121.37