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Table 1 Groupwise average accuracies of various feature extraction methods combined with various classifiers applied to classify sets A, D, and E (standard deviations are noted in parentheses).

From: Combination of EEG Complexity and Spectral Analysis for Epilepsy Diagnosis and Seizure Detection

Classifier Feature selection A D E Accuracy
LLS All features 100.00 (0.0) 95.00 (3.9) 95.50 (1.6) 96.83 (1.2)
  GA 99.25 (1.2) 94.50 (3.3) 94.75 (3.6) 96.17 (1.9)
  ApEn + AR model 98.50 (2.4) 95.50 (2.6) 95.50 (3.1) 96.50 (1.3)
LDA All features 100.00 (0.0) 94.50 (3.9) 95.75 (1.7) 96.75 (1.1)
  GA 99.50 (1.1) 95.00 (4.4) 94.50 (2.3) 96.33 (1.9)
  ApEn + AR model 97.50 (2.6) 96.00 (2.9) 95.75 (3.1) 96.41 (1.6)
BP All features 98.75 (3.1) 96.50 (2.9) 97.00 (2.0) 97.42 (1.4)
  PCA 100.0 (0.0) 97.75 (1.8) 97.00 (2.6) 98.25 (1.5)
  GA 98.50 (1.7) 91.50 (5.2) 97.50 (2.4) 95.83 (2.0)
  ApEn + AR model 99.25 (1.2) 93.00 (5.5) 89.50 (6.0) 93.92 (3.0)
LISVM All features 99.50 (1.1) 97.00 (2.6) 98.25 (1.2) 98.25 (1.1)
  PCA 99.75 (0.8) 98.00 (2.0) 97.25 (1.4) 98.33 (0.6)
  GA 98.75 (2.1) 93.50 (5.0) 98.00 (1.1) 96.75 (1.7)
  ApEn + AR model 99.75 (0.8) 94.25 (3.1) 94.50 (5.0) 96.17 (2.2)
RBFSVM All features 99.75 (0.8) 97.75 (1.8) 97.75 (1.4) 98.42 (0.8)
  PCA 99.75 (0.8) 98.25 (1.8) 98.00 (1.6) 98.67 (0.7)
  GA 99.50 (1.6) 95.00 (3.7) 96.50 (2.7) 97.00 (1.7)
  ApEn + AR model 99.75 (0.8) 92.25 (3.2) 91.75 (3.9) 94.58 (1.8)
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