Updating Geological Codes Through Iterative Jack-Knife

Abstract

We present a methodology to classify spatial data carrying only continuous variables into different categories, where categorical clustering is suitable to be applied to the data. The methodology is based in a very simple variation in the use of Bayes’ rule and the jack-knife technique. This study is mainly empirical, and is motivated by good results obtained during the application to a real case study.