# An Oversampling Method for Class Imbalance Problems on Large Datasets
## 4 Experimental Results
### Assessing the Proposed Method in Large Datasets  
In this experiment, we compared the proposed method to the fastest method in the previous experiment, namely NDO, but on larger datasets taken from the UCI repository [57] (see Table 5); these datasets are 5, 7, 10, 44, and 100 times larger than the largest dataset used in the previous experiments (page-blocks0). We followed the same evaluation scheme to measure the oversampling quality of the methods as in the previous experiment. However, given the datasets' size, the oversampling methods were applied only 10 times on each imbalanced dataset of Table 5 with a 5-fold cross-validation partition. Additionally, we only used the CART classifier because it can produce good results in a reasonable time for this size of the datasets compared with the other two supervised classifiers. \begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Dataset**} & \multicolumn{8}{c}{**Oversampling Method**} \\ \cline{2-13}  & **SMOTE** & **Borderline** & **SafeLevel** & **LNE** & **NDO** & **S-RSB* & **K-Means-S** & **Farthest-S** & **G-SMOTE** & **S-SF** & **Fast-SMOTE** \\ \hline yeast-0.3-5.9\_vs\_7-8 & 0.0154 & 0.0032 & 0.0431 & 0.0253 & 0.0012 & 0.0339 & 0.0180 & 0.0142 & 0.0197 & 0.0018 & 0.0006 \\ yeast-0.5-8.4 & 0.0155 & 0.0030 & 0.0451 & 0.0254 & 0.0013 & 0.0358 & 0.0196 & 0.0146 & 0.0226 & 0.0018 & 0.0006 \\ yeast-0.5-6.7-9\_vs\_4 & 0.0159 & 0.0035 & 0.0471 & 0.0255 & 0.0013 & 0.0352 & 0.0178 & 0.0151 & 0.0225 & 0.0019 & 0.0006 \\ wisconsin & 0.0079 & 0.0119 & 0.0306 & 0.0271 & 0.0006 & 10.9796 & 0.0095 & 0.0077 & 0.0106 & 0.0241 & 0.0003 \\ yeast-1-4.5-8\_vs\_7 & 0.0235 & 0.0032 & 0.0901 & 0.0428 & 0.0020 & 0.0630 & 0.0305 & 0.0227 & 0.0312 & 0.0017 & 0.0010 \\ abalone-9.18 & 0.0243 & 0.0037 & 0.0929 & 0.0465 & 0.0021 & 0.0700 & 0.0267 & 0.0233 & 0.0320 & 0.0021 & 0.0010 \\ jima & 0.0091 & 0.0170 & 0.0346 & 0.0338 & 0.0007 & 0.0332 & 0.0107 & 0.0087 & 0.0118 & 0.0289 & 0.0003 \\ vehicle2 & 0.0175 & 0.0167 & 0.0745 & 0.0507 & 0.0016 & 0.0877 & 0.0205 & 0.0175 & 0.0232 & 0.0236 & 0.0008 \\ vehicle1 & 0.0178 & 0.0184 & 0.0750 & 0.0501 & 0.0016 & 0.0887 & 0.0185 & 0.0174 & 0.0234 & 0.0230 & 0.0008 \\ vehicle3 & 0.0181 & 0.0190 & 0.0767 & 0.0483 & 0.0016 & 0.0989 & 0.0202 & 0.0179 & 0.0238 & 0.0221 & 0.0008 \\ vehicle0 & 0.0192 & 0.0143 & 0.0823 & 0.0625 & 0.0017 & 0.0912 & 0.0221 & 0.0188 & 0.0254 & 0.0199 & 0.0008 \\ yeast-1-2-8.9\_vs\_7 & 0.0352 & 0.0039 & 0.1494 & 0.0618 & 0.0030 & 0.1203 & 0.0413 & 0.0324 & 0.0444 & 0.0025 & 0.0015 \\ vowel0 & 0.0320 & 0.0076 & 0.1454 & 0.0656 & 0.0032 & 0.1441 & 0.0344 & 0.0310 & 0.0430 & 0.0061 & 0.0016 \\ yeast-0.2-5.7-9\_vs\_3-6-8 & 0.0316 & 0.0070 & 0.1407 & 0.0654 & 0.0027 & 0.1101 & 0.0363 & 0.0300 & 0.0421 & 0.0059 & 0.0013 \\ yeast-0.2-5.6\_vs\_3-7-8-9 & 0.0318 & 0.0074 & 0.1427 & 0.0677 & 0.0027 & 0.1092 & 0.0365 & 0.0300 & 0.0411 & 0.0059 & 0.0013 \\ yeast1 & 0.0265 & 0.0347 & 0.1342 & 0.0896 & 0.0020 & 0.1277 & 0.0292 & 0.0260 & 0.0342 & 0.0747 & 0.0010 \\ yeast4 & 0.0657 & 0.0080 & 0.2914 & 0.1040 & 0.0054 & 0.3084 & 0.0742 & 0.0523 & 0.0699 & 0.0052 & 0.0027 \\ yeast5 & 0.0562 & 0.0071 & 0.2921 & 0.1067 & 0.0054 & 0.3100 & 0.0698 & 0.0525 & 0.0706 & 0.0050 & 0.0027 \\ yeast3 & 0.0456 & 0.0136 & 0.2471 & 0.1047 & 0.0043 & 0.2384 & 0.0508 & 0.0448 & 0.0596 & 0.0141 & 0.0021 \\ yeast6 & 0.0566 & 0.0062 & 0.3081 & 0.1069 & 0.0055 & 0.3173 & 0.0803 & 0.0528 & 0.0711 & 0.0048 & 0.0028 \\ shuttle-cd-vs-c4 & 0.0634 & 0.0083 & 0.4022 & 0.1428 & 0.0068 & 0.4615 & 0.0018 & 0.0622 & 0.0864 & 0.0119 & 0.0033 \\ segment0 & 0.0821 & 0.0466 & 0.5992 & 0.3141 & 0.0105 & 1.1618 & 0.0894 & 0.0807 & 0.1045 & 0.0597 & 0.0052 \\ abalone19 & 0.1695 & 0.0255 & 1.8756 & 0.4817 & 0.0270 & 19.3115 & 0.1816 & 0.1679 & 0.2192 & 0.0262 & 0.0134 \\ page-blocks0 & 0.2206 & 0.1040 & 2.5987 & 0.7628 & 0.0344 & 28.2546 & 0.1910 & 0.2177 & 0.2792 & 0.1586 & 0.0171 \\ \hline Sum & 1.3955 & 0.4553 & 8.7356 & 3.3823 & 0.1522 & 96.2835 & 1.5021 & 1.3391 & 0.5366 & 0.5696 & 0.0754 \\ \hline \hline \end{tabular}
\end{table}