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Table 4 Correlations between classification accuracy and nearest neighbor separability

From: Classification complexity in myoelectric pattern recognition

  Average result Individual results  
  LDA (AMI) Single/OVO MLP AMI/MIX SVM AMI/MIX LDA (AMI) Single/OVO MLP AMI/MIX SVM AMI/MIX Data set
K = 20 0.86/0.98 0.96/0.97 0.90/0.90 0.83/0.93 0.92/0.92 0.72/0.72 SM
0.86/0.97 0.98/NA 0.74/NA 0.84/0.92 0.97/NA 0.70/NA IM
K = 120 0.90/0.97 0.92/0.95 0.92/0.92 0.87/0.90 0.87/0.89 0.73/0.73 SM
0.90/0.98 0.97/NA 0.78/NA 0.89/0.93 0.94/NA 0.73/NA IM
  1. The correlation between classification accuracy and NNS with different values of the parameter k. Correlations under “individual results” were calculated using classification accuracies and NNS from every individual movement, subject and feature, while those under “average result” were derived using one average NNS and classification accuracy for every subject and feature. Both methods provide one correlation, although “individual results” use more data. Classifiers were configured using AMI or MIX. Classifiers were used in the conventional “single” topology, apart from LDA, which was used in “single” and OVO. The highest correlation values per column are highlighted in bold. All correlations were found statistically significant at p < 0.01. The MIX configuration is not applicable (NA) for individual movements since there are no mixed outputs