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Table 8 Comparison of methodologies presented in the literature for the three-class (ZO-NF-S) problem

From: Spectral information of EEG signals with respect to epilepsy classification

Authors Feature extraction Classification Validation Classification accuracy
Tzallas et al. [17] (2009) TFD (SPWVD)/fractional energy ANN Monte Carlo cross-validation (50% split – 10 repeats) 97.72%
Acharya et al. [26] (2009) 10 parameters from Recurrence Quantification Analysis SVM 3-fold cross-validation 95.60%
Orhan et al. [27] (2011) DWT and K-means clustering MLP 50% train, 50% validation and test 95.60%
Acharya et al. [28] (2012) ApEn, SampEn, Phase Entropy 1 and 2 Fuzzy Sugeno Classifier Threefold cross-validation 98.10%
Peker et al. [29] (2016) Dual tree complex wavelet transform Complex valued neural networks 10-fold cross-validation 98.28%
Tiwari et al. [30] (2016) Key-point-based local binary patterns SVM 10-fold cross-validation 98.80%
Bhattacharyya et al. [31] (2017) Tunable-Q WT and K-NN entropies SVM 10-fold cross-validation 98.60%
This study Frequency sub-bands/energy, total energy, fractional energy, entropy Random forests 10-fold cross-validation 98.80%