Name
Title | ||
|---|---|---|
Automatic feature extraction using genetic programming: An application to epileptic EEG classification |
Abstract | ||
|---|---|---|
This paper applies genetic programming (GP) to perform automatic feature extraction from original feature database with the aim of improving the discriminatory performance of a classifier and reducing the input feature dimensionality at the same time. The tree structure of GP naturally represents the features, and a new function generated in this work automatically decides the number of the features extracted. In experiments on two common epileptic EEG detection problems, the classification accuracy on the GP-based features is significant higher than on the original features. Simultaneously, the dimension of the input features for the classifier is much smaller than that of the original features. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.eswa.2011.02.118 | Expert Syst. Appl. |
Keywords | Field | DocType |
genetic programming,k -nearest neighbor classifier (knn),eeg classification,classification accuracy,feature extraction,input feature,gp-based feature,epilepsy,common epileptic eeg detection,discrete wavelet transform (dwt),original feature database,automatic feature extraction,original feature,input feature dimensionality,discriminatory performance,tree structure,k nearest neighbor,discrete wavelet transform | Data mining,Pattern recognition,Eeg classification,Computer science,Feature (computer vision),Genetic programming,Curse of dimensionality,Feature extraction,Artificial intelligence,Tree structure,Classifier (linguistics),Machine learning | Journal |
Volume | Issue | ISSN |
38 | 8 | Expert Systems With Applications |
Citations | PageRank | References |
64 | 2.40 | 28 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ling Guo | 1 | 109 | 4.30 |
| Daniel Rivero | 2 | 212 | 17.59 |
| Julián Dorado | 3 | 107 | 9.14 |
| Cristian R. Munteanu | 4 | 100 | 10.27 |
| Alejandro Pazos | 5 | 273 | 38.07 |