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Table 3 Average accuracy of the classifiers (LDA, k-NN, SVM) using the proposed data extraction

From: Support system for classification of beat-to-beat arrhythmia based on variability and morphology of electrocardiogram

  Average accuracy %
  R-R \(\sigma ^{2}_{X}\) γ X κ X \(\sigma ^{2}_{X} + \gamma _{X}\) \(\sigma ^{2}_{X} + \kappa _{X}\) γX+κX \(\sigma ^{2}_{X} + \gamma _{X} + \kappa _{X}\)
Arrhythmia
LDA 84.40 92.07 91.43 93.02 96.73 99.45 99.28 99.78
k-NN 84.40 92.07 91.43 93.02 96.73 99.45 99.28 99.78
SVM 84.40 92.07 91.43 93.02 96.73 99.45 99.28 99.78
Atrial fibrillation
LDA 85.70 94.73 93.45 95.52 97.72 99.97 99.78 100
k-NN 85.70 94.73 93.45 95.52 97.72 99.97 99.78 100
SVM 85.70 94.73 93.45 95.52 97.72 99.97 99.78 100
  1. LDA linear discriminant analysis, k-NN k-nearest neighbors, SVM support vector machine, \(\left (\sigma ^{2}_{X}\right)\) variance, γX skewness, κX kurtosis