# Student Dropout Prediction for University with High Precision and Recall
## 5 Experiment and Analysis
### Analysis of Imbalanced Data Processing Methods
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Category** & **Processing** & **Accuracy** & **Dropout Recall** & **Dropout Precision** & **Dropout F1** \\ \hline \multirow{8}{*}{Undersampling} & TomekLinks & 0.990 (\(\pm\)0.00) & 0.692 (\(\pm\)0.09) & 0.952 (\(\pm\)0.05) & 0.802 (\(\pm\)0.06) \\  & RandomUndersampler & 0.990 (\(\pm\)0.04) & 0.840 (\(\pm\)0.06) & 0.202 (\(\pm\)0.09) & 0.325 (\(\pm\)0.11) \\  & NeighbourhoodCleaningRule & 0.990 (\(\pm\)0.01) & 0.701 (\(\pm\)0.08) & 0.923 (\(\pm\)0.15) & 0.757 (\(\pm\)0.10) \\  & AlikNN & 0.990 (\(\pm\)0.01) & 0.700 (\(\pm\)0.08) & 0.921 (\(\pm\)0.12) & 0.796 (\(\pm\)0.11) \\  & RepeatedEditionK NearestNeighbours & 0.990 (\(\pm\)0.02) & 0.698 (\(\pm\)0.08) & 0.926 (\(\pm\)0.12) & 0.796 (\(\pm\)0.10) \\  & EditedNearestNeighbours & 0.990 (\(\pm\)0.02) & 0.698 (\(\pm\)0.08) & 0.926 (\(\pm\)0.12) & 0.796 (\(\pm\)0.10) \\  & ClusterControids & 0.232 (\(\pm\)0.09) & 0.951 (\(\pm\)0.07) & 0.034 (\(\pm\)0.11) & 0.065 (\(\pm\)0.12) \\ \hline \multirow{8}{*}{Oversampling} & SMOTE & 0.990 (\(\pm\)0.03) & 0.698 (\(\pm\)0.07) & 0.947 (\(\pm\)0.10) & 0.803 (\(\pm\)0.10) \\  & BorderlineSMOTE & 0.990 (\(\pm\)0.05) & 0.695 (\(\pm\)0.07) & 0.940 (\(\pm\)0.11) & 0.799 (\(\pm\)0.12) \\  & ADASYN & 0.990 (\(\pm\)0.05) & 0.696 (\(\pm\)0.07) & 0.945 (\(\pm\)0.11) & 0.802 (\(\pm\)0.12) \\  & RandomOverSampler & 0.985 (\(\pm\)0.05) & 0.726 (\(\pm\)0.07) & 0.749 (\(\pm\)0.11) & 0.737 (\(\pm\)0.12) \\  & SVNSMOTE & 0.990 (\(\pm\)0.05) & 0.698 (\(\pm\)0.07) & 0.946 (\(\pm\)0.11) & 0.803 (\(\pm\)0.12) \\ \hline \multirow{2}{*}{Combined} & SMOTENN & 0.990 (\(\pm\)0.02) & 0.702 (\(\pm\)0.07) & 0.914 (\(\pm\)0.10) & 0.794 (\(\pm\)0.10) \\  & SMOTETOMEK & 0.990 (\(\pm\)0.03) & 0.691 (\(\pm\)0.07) & 0.956 (\(\pm\)0.10) & 0.803 (\(\pm\)0.10) \\ \hline \multirow{2}{*}{Proposed} & RSMOTENN & 0.988 (\(\pm\)0.03) & 0.714 (\(\pm\)0.07) & 0.828 (\(\pm\)0.10) & 0.767 (\(\pm\)0.10) \\ \hline \end{tabular}
\end{table} 
Table 9: Performance of XGBost with Imbalanced Data Processing. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Category** & **Processing** & **Accuracy** & **Dropout Recall** & **Dropout Precision** & **Dropout F1** \\ \hline \multirow{8}{*}{Undersampling} & TomeLinks & 0.990 (4.004) & 0.686 (4.009) & 0.948 (4.006) & 0.796 (4.006) \\  & RandomUnderSampler & 0.942 (4.003) & 0.774 (4.008) & 0.294 (4.12) & 0.427 (4.012) \\  & NeighbourhoodCleaningRule & 0.989 (0.07) & 0.687 (0.08) & 0.918 (4.011) & 0.786 (4.008) \\  & AlNNN & 0.990 (4.001) & 0.690 (4.008) & 0.948 (4.07) & 0.798 (4.006) \\  & RepeatedE(EdibleNearestNeighbours & 0.990 (4.001) & 0.685 (0.09) & 0.951 (4.008) & 0.796 (4.007) \\  & EditedNearestNeighbours & 0.989 (4.001) & 0.690 (4.009) & 0.952 (4.008) & 0.788 (4.007) \\  & ClusterCentroids & 0.507 (4.001) & 0.948 (4.009) & 0.050 (4.008) & 0.095 (4.008) \\ \hline \multirow{8}{*}{Oversampling} & SMOTE & 0.987 (4.001) & 0.691 (0.09) & 0.821 (4.008) & 0.751 (4.008) \\  & BorderinsMOTE & 0.982 (4.001) & 0.705 (4.009) & 0.665 (4.008) & 0.685 (4.008) \\  & ADASYN & 0.957 (4.001) & 0.745 (4.009) & 0.369 (4.008) & 0.493 (4.008) \\  & RandomOverSampler & 0.947 (4.001) & 0.800 (4.009) & 0.318 (4.008) & 0.455 (4.008) \\  & SVNASOTE & 0.984 (4.01) & 0.700 (4.009) & 0.727 (4.008) & 0.714 (4.008) \\ \hline \multirow{2}{*}{Combined} & SMOTENN & 0.986 (4.001) & 0.700 (4.009) & 0.776 (4.009) & 0.756 (4.008) \\  & SMOTETOMEK & 0.990 (4.001) & 0.686 (4.009) & 0.949 (4.008) & 0.796 (4.007) \\ \hline \multirow{2}{*}{Proposed} & RSMOTENN & 0.967 (4.001) & 0.752 (4.009) & 0.450 (4.008) & 0.563 (4.007) \\ \hline \end{tabular}
\end{table} 
Table 11. Performance of CatBoost with Imbalanced Data Processing.