Prospectivity mapping of Iron Oxide-Copper-Gold (IOCG) deposits using support vector machine method in Feyzaabad area (east of Iran)

Feyzaabad area is situated in the northeastern part of iran that hosts mainly iron oxide copper-gold (iocg) mineralization. in the present study,support vector machine (svm),as a supervised classification method in mineral prospectivity mapping,is applied in 1:100000 feyzaabad area,in east of iran. different evidential layers such as hydrothermal alteration,geological and geochemical data were integrated to generate prospectivity model for iocg mineralization. the outcomes of the svm method show that prospective target areas for iocg deposits are defined mainly by vicinity to ne–sw trending faults and pyroclastic rocks (mainly tuff) and au-cu geochemical anomalies. these outcomes show that svm is a potentially effective method in order to integrate multiple information evidence layers in predictive mapping of mineral prospectivity.the final prospectivity model investigation demonstrate that beside identifying known iocg deposits,which were applied as training regions in the applied method to evaluate the svm,the applied method has specified some new targets as well. so the target areas shown in the final prospectivity model can be applied for follow-up exploration of the iocg deposits. © 2016,national centre of excellence in geology. all rights reserved.