An adaptable Random Forest model for the declustering of earthquake catalogs

Random Forest models trained on different proportion of the synthetic earthquake catalog data set. The name of the model is defined as RF_XP_Y_Z.sav where: - X is the number of neighbor considered in the training stage; - Y is the number of feature considered in the training stage; - Z is the percentage (0-100) of the total data set used for the training stage. More details on how to use the model in this Github page.