# An Empirical Assessment of Performance of Data Balancing Techniques in Classification Task
## 4 Results and Discussion
### Performance of DBT
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Dataset** & **None** & **US** & **OS** & **HS** & **ROSE** & **SMOTE** & **CBUS** \\ \hline Pima & 0.701887 & 0.731792 & 0.720189 & 0.704057 & 0.686321 & 0.728491 & 0.736792 \\ \hline ecoli1 & 0.9 & 0.931373 & 0.947059 & 0.941176 & 0.911765 & 0.937255 & 0.95098 \\ \hline segment0 & 0.976923 & 1 & 1 & 0.992308 & 0.865823 & 0.992308 & 1 \\ \hline yeast3 & 0.844223 & 0.923295 & 0.875473 & 0.887311 & 0.827652 & 0.902936 & 0.904356 \\ \hline vowel0 & 0.997207 & 0.977654 & 0.997207 & 0.997207 & 0.958101 & 0.997207 & 0.980447 \\ \hline glass2 & 0.5 & 0.833333 & 0.628205 & 0.807692 & 0.717949 & 0.628205 & 0.74359 \\ \hline yeast-l\_vs\_7 & 0.660784 & 0.745098 & 0.583333 & 0.577451 & 0.505882 & 0.654902 & 0.84375 \\ \hline ecoli4 & 0.992063 & 0.960317 & 0.992063 & 0.992063 & 0.911765 & 0.992063 & 0.912698 \\ \hline glass-0-1-6\_vs\_5 & 0.5 & 0.842857 & 0.5 & 1 & 0.957143 & 1 & 0.957143 \\ \hline page-blocks-1-3\_vs\_4 & 1 & 1 & 1 & 1 & 0.977273 & 0.9 & 0.988636 \\ \hline yeast-1-4-5-8\_vs\_7 & 0.5 & 0.556818 & 0.503788 & 0.575758 & 0.511364 & 0.518939 & 0.556818 \\ \hline yeast-2\_vs\_8 & 0.875 & 0.701087 & 0.744565 & 0.744565 & 0.652174 & 0.733696 & 0.711957 \\ \hline yeast4 & 0.548252 & 0.71958 & 0.598252 & 0.686014 & 0.505245 & 0.734266 & 0.804895 \\ \hline winequality-red-4 & 0.5 & 0.613916 & 0.503236 & 0.512945 & 0.633657 & 0.532201 & 0.68123 \\ \hline poker-9\_vs\_7 & 0.5 & 0.946809 & 0.5 & 0.5 & 0.925532 & 0.5 & 0.595745 \\ \hline yeast-1-2-8-9\_vs\_7 & 0.580601 & 0.605191 & 0.583333 & 0.577869 & 0.510929 & 0.572404 & 0.610656 \\ \hline winequality-white-9\_vs\_4 & 0.5 & 0.984375 & 0.5 & 0.5 & 0.984375 & 1 & 0.84375 \\ \hline yeast5 & 0.873264 & 0.907986 & 0.873264 & 0.932292 & 0.951389 & 0.873264 & 0.958333 \\ \hline winequality-red-8\_vs\_6 & 0.666667 & 0.769461 & 0.663673 & 0.654691 & 0.728543 & 0.651697 & 0.751497 \\ \hline ecoli-0-1-3-7\_vs\_2-6 & 0.509259 & 0.916667 & 0.5 & 0.5 & 0.527778 & 0.5 & 0.564815 \\ \hline abalone-21\_vs\_8 & 0.75 & 0.946903 & 1 & 1 & 0.986726 & 0.99115 & 0.982301 \\ \hline \end{tabular}
\end{table} 
Table 6: Performance of DBT for RF. \begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Dataset** & **None** & **US** & **OS** & **HS** & **ROSE** & **SMOTE** & **CBUS** \\ \hline yeast-1-2-8-9\_vs\_7 & 0.5 & 0.674863 & 0.5 & 0.508197 & 0.569672 & 0.502732 & 0.520492 \\ \hline winequality-white-9\_vs\_4 & 1 & 0.90625 & 1 & 0.96875 & 0.875 & 0.984375 & 0.859375 \\ \hline yeast5 & 0.5 & 0.892361 & 0.864583 & 0.864583 & 0.859375 & 0.807292 & 0.946181 \\ \hline winequality-red-8\_vs\_6 & 0.51497 & 0.682635 & 0.582834 & 0.567864 & 0.537924 & 0.582834 & 0.613772 \\ \hline ecoli-0-1-3-7\_vs\_2-6 & 0.5 & 0.907407 & 0.5 & 0.5 & 0.5 & 0.5 & 0.5 \\ \hline abalone-21\_vs\_8 & 0.973451 & 0.90708 & 0.938053 & 0.946903 & 0.942478 & 0.938053 & 0.933628 \\ \hline yeast6 & 0.5 & 0.857637 & 0.850222 & 0.853683 & 0.775334 & 0.782254 & 0.793129 \\ \hline winequality-white-3\_vs\_7 & 0.744318 & 0.792614 & 0.715909 & 0.849432 & 0.744318 & 0.696023 & 0.596591 \\ \hline winequality-red-8\_vs\_6-7 & 0.51497 & 0.682635 & 0.582834 & 0.567864 & 0.537924 & 0.582834 & 0.613772 \\ \hline abalone-19\_vs\_10-11-12-13 & 0.5 & 0.646226 & 0.558176 & 0.548742 & 0.514151 & 0.525157 & 0.561321 \\ \hline Average AUC Score & 0.632837 & 0.788691 & 0.718937 & 0.72299 & 0.714321 & 0.757164 & 0.73301 \\ \hline Mean Rank & 5.54(7) & 2.72(1) & 3.98(4) & 4.02(5) & 4.60(6) & 3.44(2) & 3.70(3) \\ \hline [PERSON] test statistics & \multicolumn{6}{c}{Friedman chi-squared = 27.272, df = 6, \(p\)-value = 0.0001288} \\ \hline \end{tabular}
\end{table} 
Table 5: _Cont._