TY - GEN
T1 - EEG feature selection using mutual information and support vector machine
T2 - 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
AU - Guerrero-Mosquera, Carlos
AU - Verleysen, Michel
AU - Navia Vazquez, Angel
PY - 2010
Y1 - 2010
N2 - The large number of methods for EEG feature extraction demands a good choice for EEG features for every task. This paper compares three subsets of features obtained by tracks extraction method, wavelet transform and fractional Fourier transform. Particularly, we compare the performance of each subset in classification tasks using support vector machines and then we select possible combination of features b y feature selection methods based on forward-backward procedure and mutual information as relevance criteria. Results confirm that fractional Fourier transform coefficients present very good performance and also the possibility of using some combination of this features to improve the performance of the classifier. To reinforce the relevance of the study, we carry out 1000 independent runs using a bootstrap approach, and evaluate the statistical significance of the Fscore results using the Kruskal-Wallis test.
AB - The large number of methods for EEG feature extraction demands a good choice for EEG features for every task. This paper compares three subsets of features obtained by tracks extraction method, wavelet transform and fractional Fourier transform. Particularly, we compare the performance of each subset in classification tasks using support vector machines and then we select possible combination of features b y feature selection methods based on forward-backward procedure and mutual information as relevance criteria. Results confirm that fractional Fourier transform coefficients present very good performance and also the possibility of using some combination of this features to improve the performance of the classifier. To reinforce the relevance of the study, we carry out 1000 independent runs using a bootstrap approach, and evaluate the statistical significance of the Fscore results using the Kruskal-Wallis test.
UR - http://www.scopus.com/inward/record.url?scp=78650822497&partnerID=8YFLogxK
U2 - 10.1109/IEMBS.2010.5627239
DO - 10.1109/IEMBS.2010.5627239
M3 - Conference contribution
C2 - 21096669
AN - SCOPUS:78650822497
SN - 9781424441235
T3 - 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
SP - 4946
EP - 4949
BT - 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Y2 - 31 August 2010 through 4 September 2010
ER -