# Large Earthquake Prediction in Chile with Imbalanced Classifiers and Ensemble Learning
## 5 Conclusions  
Large magnitude earthquake prediction has been addressed in this work by means of imbalanced classifiers and ensemble learning. As a case study, four cities of Chile (Santiago, Valparaiso, Talca and Pichilemu) have been analyzed, and new imbalanced datasets have been created, using as target label if a large earthquake is occurring or not within the next five days. During the generation of the new datasets, it was found that data from Pichilemu could not be used and, therefore, its study has not been done. Achieved results show meaningful improvement in the three remaining cities when compared to previous works, especially in terms of specificity and PPV. The main limitation of the study carried out is the size of the datasets used, being highly desired to use catalogs with longer historical data for further analysis. Future work is directed towards the generalization of the method, whose promising performance has been reported, by its application across different seismic zones of the world. The authors would like to thank the Spanish Ministry of Economy and Competitiveness, Junta de Andalucia for the support under projects TIN2014-55894-C2-R and P12-TIC-1728, respectively. Additionally, the authors want to express their gratitude to NT2 Labs (Chile) and Morales-Esteban for their support and helpful comments. [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] contributed reagents/materials/analysis tools; [PERSON] and [PERSON] wrote the paper. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline
**Inseable** & **TP** & **FP** & **TN** & **FN** & \(\mathbf{S_{n}}\) & \(\mathbf{S_{p}}\) & **PPV** & **PPV** & **F** & **AUC** & **MCC** & **GM** \\ \hline
1, 2 & 5 & 0 & 100 & 0 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\
2, 3 & 5 & 0 & 100 & 0 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\
2, 5 & 5 & 0 & 100 & 0 & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1 \\
2, 8 & 4 & 0 & 100 & 1 & 0.80 & 1 & 1 & 0.99 & 0.95 & 0.94 & 0.89 & 0.90 \\
1, 9 & 3 & 0 & 100 & 2 & 0.60 & 1 & 1 & 0.98 & 0.90 & 0.87 & 0.77 & 0.78 \\ \hline Average & 4.5 & 0 & 100 & 0.5 & 0.9 & 1 & 1 & 0.99 & 0.98 & 0.97 & 0.96 & 0.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Ensembles generated for Talca. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline
**Index** & **Preprocessing** & **Classifier** & **TP** & **FP** & **TN** & **FN** & \(\mathbf{S_{n}}\) & \(\mathbf{S_{p}}\) & **PPV** & **PPV** & **F** & **AUC** & **MCC** & **GM** \\ \hline
1 & ADASYN & NNCS & 5 & 7 & 93 & 0 & 1 & 0.93 & 0.42 & 1 & 0.78 & 0.97 & 0.62 & 0.96 \\
2 & CPM & C45 CS & 5 & 19 & 81 & 0 & 1 & 0.81 & 0.21 & 1 & 0.62 & 0.90 & 0.41 & 0.90 \\
3 & ADASYN & Bagging & 5 & 21 & 79 & 0 & 1 & 0.79 & 0.19 & 1 & 0.60 & 0.89 & 0.39 & 0.89 \\
4 & ADASYN & UnderOverBagging & 5 & 23 & 77 & 0 & 1 & 0.77 & 0.18 & 1 & 0.59 & 0.88 & 0.37 & 0.88 \\
5 & ADASYN & OverBagging & 5 & 23 & 77 & 0 & 1 & 0.77 & 0.18 & 1 & 0.59 & 0.88 & 0.37 & 0.88 \\
6 & SPIDER2 & NNCS & 4 & 15 & 85 & 1 & 1 & 0.85 & 0.21 & 0.99 & 0.62 & 0.82 & 0.36 & 0.83 \\
7 & CPM & NNCS & 4 & 18 & 82 & 1 & 1 & 0.82 & 0.18 & 0.99 & 0.60 & 0.81 & 0.32 & 0.81 \\
8 & SMOTE-TL & EasyEnsemble & 4 & 24 & 76 & 1 & 1 & 0.76 & 0.14 & 0.99 & 0.55 & 0.78 & 0.27 & 0.78 \\
9 & NCI & UnderBagging & 3 & 5 & 95 & 2 & 1 & 0.95 & 0.38 & 0.98 & 0.71 & 0.78 & 0.44 & 0.76 \\
10 & SMOTE & BalanceCascade & 3 & 6 & 94 & 2 & 1 & 0.94 & 0.33 & 0.93 & 0.69 & 0.77 & 0.41 & 0.75 \\
11 & Borderline-SMOTE & UnderBagging & 3 & 7 & 93 & 2 & 1 & 0.93 & 0.30 & 0.98 & 0.68 & 0.77 & 0.39 & 0.75 \\
12 & NCI & Bagging & 3 & 8 & 92 & 2 & 1 & 0.92 & 0.27 & 0.98 & 0.66 & 0.76 & 0.36 & 0.74 \\
13 & TL & NNCS & 5 & 49 & 51 & 0 & 1 & 0.51 & 0.09 & 1 & 0.42 & 0.75 & 0.22 & 0.71 \\
14 & RUS & BalanceCascade & 3 & 11 & 89 & 2 & 1 & 0.89 & 0.21 & 0.98 & 0.62 & 0.74 & 0.31 & 0.73 \\
15 & CPM & AdaBoost & 3 & 12 & 88 & 2 & 1 & 0.88 & 0.20 & 0.98 & 0.61 & 0.74 & 0.29 & 0.73 \\ \hline \hline \end{tabular}
\end{table}