# Dynamic Ensemble Selection for EEG Signal Classification in Distributed Data Environments
## 3 Datasets and Experimental Results
**} & \multicolumn{1}{c}{**Recall**} & \multicolumn{1}{c}{**F1**} & \multicolumn{1}{c}{**(Macro)**} & \multicolumn{1}{c}{**BAacc**} & \multicolumn{1}{c}{**Acc**} \\ \hline
9 LT & Abstract level; sum; RF (200,gini) & 0.918 & 0.887 & 0.882 & 0.882 & 0.887 & 0.887 \\  & Measurement level; sum; RF (20,gini) & 0.906 & 0.86 & 0.85 & 0.85 & 0.86 & 0.86 \\  & Unified groups; abstract level; RF (200,gini) & 0.918 & 0.887 & 0.882 & 0.882 & 0.887 & 0.887 \\  & Diverse groups; abstract level; RF (200,gini) & 0.849 & 0.827 & 0.824 & 0.824 & 0.827 & 0.827 \\  & Unified groups; measurement level; RF (10,gini) & 0.907 & 0.867 & 0.859 & 0.859 & 0.867 & 0.867 \\  & Diverse groups; measurement level; RF (20,entropy) & 0.884 & 0.84 & 0.83 & 0.83 & 0.84 & 0.84 \\  & Abstract level; sum; kNN (6) & 0.707 & 0.687 & 0.664 & 0.664 & 0.687 & 0.687 \\  & Measurement level; sum; kNN (6) & 0.776 & 0.687 & 0.664 & 0.664 & 0.687 & 0.687 \\  & Diverse groups; abstract level; kNN (6) & 0.788 & 0.727 & 0.681 & 0.681 & 0.727 & 0.727 \\  & Unified groups; measurement level; kNN (6) & 0.776 & 0.687 & 0.664 & 0.664 & 0.687 & 0.687 \\  & Diverse groups; measurement level; kNN (2) & 0.727 & 0.687 & 0.694 & 0.694 & 0.687 & 0.687 \\  & Abstract level; sum; AdaBoost (100) & 0.953 & 0.94 & 0.939 & 0.939 & 0.94 & 0.94 \\  & Measurement level; sum; AdaBoost (50) & 0.934 & 0.927 & 0.926 & 0.926 & 0.927 & 0.927 \\  & Unified groups; abstract level; AdaBoost (50) & 0.938 & 0.927 & 0.926 & 0.926 & 0.927 & 0.927 \\  & Diverse groups; abstract level; AdaBoost (100) & 0.747 & 0.713 & 0.714 & 0.713 & 0.713 \\  & Unified groups; measurement level; AdaBoost (20) & 0.928 & 0.92 & 0.92 & 0.92 & 0.92 & 0.92 \\  & Diverse groups; measurement level; AdaBoost (10) & 0.912 & 0.893 & 0.892 & 0.892 & 0.893 & 0.893 \\  & Abstract level; sum; Gradient Boosting (10) & 0.967 & 0.96 & 0.959 & 0.959 & 0.96 & 0.96 \\  & Measurement level; sum; Gradient Boosting (10) & 0.964 & 0.953 & 0.952 & 0.952 & 0.953 & 0.953 \\  & Unified groups; abstract level; Gradient Boosting (10) & 0.985 & 0.98 & 0.98 & 0.98 & 0.98 & 0.98 \\  & Diverse groups; abstract level; Gradient Boosting (20) & 0.672 & 0.653 & 0.655 & 0.655 & 0.653 & 0.653 \\  & Unified groups; measurement level; Gradient Boosting (10) & 0.989 & **0.987** & 0.987 & 0.987 & 0.987 & 0.987 \\  & Diverse groups; measurement level; Gradient Boosting (100) & 0.763 & 0.733 & 0.738 & 0.738 & 0.733 & 0.733 \\  & Abstract level; sum; Logistic Regression & 0.782 & 0.767 & 0.765 & 0.765 & 0.767 & 0.767 \\  & Measurement level; sum; Logistic Regression & 0.791 & 0.78 & 0.776 & 0.776 & 0.78 & 0.78 \\  & Unified groups; abstract level; Logistic Regression & 0.771 & 0.74 & 0.742 & 0.742 & 0.74 & 0.74 \\  & Diverse groups; abstract level; Logistic Regression & 0.541 & 0.553 & 0.535 & 0.535 & 0.553 \\  & Unified groups; measurement level; Logistic Regression & 0.779 & 0.733 & 0.739 & 0.733 & 0.733 \\  & Diverse groups; measurement level; Logistic Regression & 0.712 & 0.58 & 0.577 & 0.577 & 0.58 & 0.58 \\ \hline
11 LT & Abstract level; sum; RF (100,entropy) & 0.879 & 0.807 & 0.787 & 0.787 & 0.807 & 0.807 \\  & Measurement level; sum; RF (10,gini) & 0.882 & 0.82 & 0.793 & 0.793 & 0.82 & 0.82 \\  & Unified groups; abstract level; RF (200,gini) & 0.861 & 0.8 & 0.78 & 0.78 & 0.8 & 0.8 \\  & Diverse groups; abstract level; RF (20,gini) & 0.749 & 0.713 & 0.698 & 0.698 & 0.713 & 0.713 \\  & Unified groups; measurement level; RF (100,gini) & 0.882 & 0.813 & 0.795 & 0.795 & 0.813 & 0.813 \\  & Diverse groups; measurement level; RF (100,entropy) & 0.889 & 0.827 & 0.81 & 0.81 & 0.827 & 0.827 \\  & Abstract level; sum; kNN (2) & 0.742 & 0.62 & 0.527 & 0.527 & 0.62 & 0.62 \\  & Measurement level; sum; kNN (5) & 0.594 & 0.613 & 0.563 & 0.563 & 0.613 & 0.613 \\  & Unified groups; abstract level; kNN (2) & 0.742 & 0.62 & 0.527 & 0.527 & 0.62 & 0.62 \\  & Diverse groups; abstract level; kNN (2) & 0.673 & 0.64 & 0.641 & 0.641 & 0.64 & 0.64 \\  & Unified groups; measurement level; kNN (5) & 0.594 & 0.613 & 0.563 & 0.563 & 0.613 & 0.613 \\  & Diverse groups; measurement level; kNN (3) & 0.818 & 0.707 & 0.679 & 0.679 & 0.707 & 0.707 \\  & Abstract level; sum; AdaBoost (50) & 0.924 & 0.92 & 0.92 & 0.92 & 0.92 & 0.92 \\  & Measurement level; sum; AdaBoost (100) & 0.938 & 0.92 & 0.918 & 0.918 & 0.92 & 0.92 \\  & Unified groups; abstract level; AdaBoost (50) & 0.89 & 0.88 & 0.879 & 0.879 & 0.88 & 0.88 \\  & Diverse groups; abstract level; AdaBoost (10) & 0.709 & 0.64 & 0.637 & 0.637 & 0.64 & 0.64 \\  & Unified groups; measurement level; AdaBoost (50) & 0.932 & 0.92 & 0.918 & 0.918 & 0.92 & 0.92 \\  & Diverse groups; measurement level; AdaBoost (20) & 0.786 & 0.74 & 0.721 & 0.721 & 0.74 & 0.74 \\  & Abstract level; sum; Gradient Boosting (10) & 0.87 & 0.833 & 0.82  
The experimental results for the EEG Epilepsy dataset presented in Tables 1 and 2 provide clear evidence supporting the effectiveness of the proposed approach based on dynamic ensemble selection over distributed EEG data sources.