## 2 Results
### EMD-Based Analysis of the HRV Signals
 } & CSS & FLM & 61.00 \(\pm\) 10.49\% & 0.641 \(\pm\) 0.122 & 60.82 \(\pm\) 9.93\% & 62.00 \(\pm\) 10.81\% & 65.00 \(\pm\) 16.50\% & 57.00 \(\pm\) 17.67\% \\ \cline{2-8}  & CM PCA & GLM & 61.00 \(\pm\) 11.01\% & 0.618 \(\pm\) 0.119 & 61.51 \(\pm\) 12.96\% & 61.28 \(\pm\) 11.86\% & 63.00 \(\pm\) 16.36\% & 59.00 \(\pm\) 15.95\% \\ \cline{2-8}  & CM ICA & GBT & 61.00 \(\pm\) 12.65\% & 0.620 \(\pm\) 0.120 & 62.80 \(\pm\) 12.95\% & 61.03 \(\pm\) 12.38\% & 62.00 \(\pm\) 15.49\% & 60.00 \(\pm\) 22.11\% \\ \cline{2-8}  & CM SVD & GBT & 60.00 \(\pm\) 10.27\% & 0.657 \(\pm\) 0.104 & 60.34 \(\pm\) 11.56\% & 59.77 \(\pm\) 11.17\% & 60.00 \(\pm\) 13.33\% & 60.00 \(\pm\) 14.14\% \\ \cline{2-8}  & Correlation & RF & 62.50 \(\pm\) 9.50\% & 0.651 \(\pm\) 0.133 & 67.60 \(\pm\) 13.48\% & 57.26 \(\pm\) 11.19\% & 51.00 \(\pm\) 12.87\% & 74.00 \(\pm\) 15.06\% \\ \cline{2-8}  & Deviation & GBT & 67.00 \(\pm\) 10.06\% & 0.680 \(\pm\) 0.123 & 70.79 \(\pm\) 12.86\% & 65.57 \(\pm\) 9.48\% & 63.00 \(\pm\) 11.60\% & 71.00 \(\pm\) 18.53\% \\ \cline{2-8}  & GI & LR & 61.00 \(\pm\) 4.59\% & 0.622 \(\pm\) 0.079 & 62.28 \(\pm\) 8.07\% & 60.49 \(\pm\) 6.14\% & 61.00 \(\pm\) 12.87\% & 61.00 \(\pm\) 13.70\% \\ \cline{2-8}  & IG & GBT & 67.00 \(\pm\) 9.78\% & 0.694 \(\pm\) 0.104 & 71.45 \(\pm\) 15.07\% & 64.83 \(\pm\) 12.18\% & 64.00 \(\pm\) 20.66\% & 70.00 \(\pm\) 21.08\% \\ \cline{2-8}  & IGR & LR & 58.00 \(\pm\) 9.78\% & 0.628 \(\pm\) 0.133 & 59.22 \(\pm\) 10.93\% & 57.33 \(\pm\) 12.12\% & 59.00 \(\pm\) 18.53\% & 57.00 \(\pm\) 19.47\% \\ \cline{2-8}  & PCA & FLM & 64.00 \(\pm\) 9.37\% & 0.672 \(\pm\) 0.132 & 63.42 \(\pm\) 9.97\% & 66.25 \(\pm\) 8.68\% & 71.00 \(\pm\) 12.87\% & 57.00 \(\pm\) 18.89\% \\ \cline{2-8}  & Relief & GBT & 65.00 \(\pm\) 11.30\% & 0.698 \(\pm\) 0.117 & 68.56 \(\pm\) 14.11\% & 62.92 \(\pm\) 11.60\% & 60.00 \(\pm\) 14.14\% & 70.00 \(\pm\) 17.64\% \\ \cline{2-8}  & Rule & GBT & 62.50 \(\pm\) 11.61\% & 0.661 \(\pm\) 0.153 & 62.70 \(\pm\) 11.32\% & 61.79 \(\pm\) 12.92\% & 62.00 \(\pm\) 16.19\% & 63.00 \(\pm\) 14.18\% \\ \cline{2-8}  & SVM & FLM & 59.50 \(\pm\) 13.43\% & 0.614 \(\pm\) 0.154 & 59.25 \(\pm\) 11.98\% & 57.66 \(\pm\) 15.18\% & 57.00 \(\pm\) 18.89\% & 62.00 \(\pm\) 12.29\% \\ \cline{2-8}  & TI & DL & 60.50 \(\pm\) 12.12\% & 0.631 \(\pm\) 0.144 & 57.90 \(\pmThe GBT models generated using the ten important parameters obtained from the \"Deviation\" and \"IG\" parameter ranking methods exhibited an accuracy of 67.00 \(\pm\) 10.06% and 67.00 \(\pm\) 9.78%, respectively. Although the mean value of the accuracy was the same in both the models, the standard deviation (SD) of the IG-based GBT model was relatively lower than that of the Deviation-based GBT model. Hence, the IG-based GBT model was selected as the most suitable model for automatic identification of cannabis consumers using EMD-based processing of the HRV signals. The GBT model is an ensemble of either classification or regression trees, which uses boosting to provide the results with progressively improved estimations [18]. The proposed GBT model generated 20 classification trees to provide the final classification result. A typical classification tree among them has been shown in Figure 2.