# Impact of Imbalanced Datasets Preprocessing in the Performance of Associative Classifiers
## 5 Experimental Results
### Impact of the Sampling Algorithms in the Performance of Associative Classifiers
#### 5.2.1 Impact of the Sampling Algorithms on the Performance of Associative Classifiers  
The AUC results for the HACT classifier are presented in Tables 9-11 below. The good results (AUC improvements) are highlighted in bold, while the results that present less AUC than the original set (imbalanced) are underlined. Figure 4: Characteristics of the compared methods. The oversampling algorithms had slight drops and increases in the classifier performance, but no clear advantage was shown in the results. However, to determine if these differences in performance are significant or not, statistical tests were applied (Section 5.3). A similar behavior was observed for undersampling algorithms, having slight drops and increases in the classifier performance, but with no clear advantages. Due to the SBC algorithm deleted the \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Datasets** & **Original** & **CNNTL** & **NCL** & **OSS** & **RUS** & **SBC** & **TL** \\ \hline Australian & 0.59 & 0.58 & 0.59 & 0.57 & 0.59 & **0.64** & 0.59 \\ Default credit & 0.95 & 0.89 & 0.95 & 0.88 & **0.96** & - & 0.95 \\ German & 0.64 & 0.64 & 0.63 & 0.64 & 0.64 & 0.50 & 0.64 \\ Give me credit & 0.64 & 0.62 & 0.63 & 0.61 & 0.63 & 0.64 & 0.63 \\ Iranian & 0.61 & 0.61 & 0.61 & 0.61 & - & 0.61 \\ Japanese & 0.64 & 0.64 & **0.65** & **0.67** & **0.65** & 0.50 & 0.64 \\ Polish\_1 & 0.66 & 0.62 & 0.61 & 0.61 & 0.66 & - & 0.62 \\ Polish\_2 & 0.58 & 0.58 & 0.58 & 0.58 & 0.58 & - & 0.58 \\ Polish\_3 & 0.52 & 0.50 & 0.52 & 0.51 & 0.51 & - & 0.52 \\ Polish\_4 & 0.50 & 0.49 & 0.50 & 0.50 & 0.50 & - & 0.50 \\ Polish\_5 & 0.53 & 0.52 & 0.53 & 0.52 & 0.53 & - & 0.53 \\ Qualitative & 0.55 & 0.55 & **0.56** & 0.55 & **0.56** & - & 0.55 \\ The PAKDD & 0.62 & **0.63** & 0.62 & **0.63** & 0.62 & 0.53 & **0.63** \\ \hline \hline \end{tabular}
\end{table} 
Table 10: AUC for HACT classifier after undersampling algorithms. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Datasets** & **Original** & **SMOTE-ENN** & **SMOTE-TL** & **SPIDER2** & **SPIDER** \\ \hline Australian & 0.59 & **0.60** & 0.57 & 0.59 & 0.59 \\ Default credit & 0.95 & **0.96** & **0.96** & 0.95 & 0.95 \\ German & 0.64 & 0.63 & 0.63 & 0.62 & 0.63 \\ Give me credit & 0.63 & 0.63 & 0.63 & 0.63 & 0.63 \\ Iranian & 0.61 & 0.61 & 0.61 & 0.61 & 0.61 \\ Japanese & 0.64 & 0.64 & **0.65** & **0.65** & **0.65** \\ Polish\_1 & 0.70 & 0.65 & 0.62 & 0.60 & 0.62 \\ Polish\_2 & 0.58 & 0.58 & 0.58 & 0.58 & 0.58 \\ Polish\_3 & 0.52 & 0.52 & 0.52 & **0.53** & 0.52 \\ Polish\_4 & 0.50 & 0.50 & 0.50 & 0.50 & 0.50 \\ Polish\_5 & 0.53 & 0.52 & 0.52 & 0.52 & 0.53 \\ Qualitative & 0.55 & **0.56** & **0.56** & 0.55 & 0.55 \\ The PAKDD & 0.62 & 0.62 & 0.62 & 0.62 & **0.63** \\ \hline \hline \end{tabular}
\end{table} 
Table 11: AUC for HACT classifier after hybrid algorithms. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Datasets** & **Original** & **ADASYN** & **ADOMS** & **SMOTE-BL** & **ROS** & **SMOTE-SL** & **SMOTE** \\ \hline Australian & 0.59 & 0.59 & 0.59 & 0.59 & **0.61** & 0.59 & **0.60** \\ Default credit & 0.95 & **0.96** & **0.96** & **0.96** & **0.96** & **0.96** & **0.97** \\ German & 0.64 & 0.63 & 0.64 & 0.64 & 0.64 & 0.64 & 0.64 \\ Give me credit & 0.63 & 0.63 & 0.60 & 0.63 & **0.64** & 0.63 & 0.62 \\ Iranian & 0.61 & 0.60 & 0.61 & 0.60 & 0.61 & 0.60 & 0.60 \\ Japanese & 0.64 & 0.65 & 0.64 & **0.66** & 0.64 & 0.62 & 0.63 \\ Polish\_1 & 0.70 & 0.65 & 0.66 & 0.62 & 0.65 & 0.64 & 0.66 \\ Polish\_2 & 0.58 & 0.58 & 0.58 & 0.58 & 0.58 & 0.58 & 0.58 \\ Polish\_3 & 0.52 & **0.53** & 0.52 & 0.51 & 0.52 & **0.53** & 0.52 \\ Polish\_4 & 0.50 & 0.50 & 0.50 & 0.50 & 0.50 & 0.50 \\ Polish\_5 & 0.53 & 0.52 & 0.52 & 0.53 & 0.52 & 0.52 & 0.52 \\ Qualitative & 0.  
majority class in several datasets, its results in such data were not computed. Again, to determine if these differences in performance are significant or not, statistical tests were applied (Section 5.3).