One of the most important viewpoints of data mining concerning the analysis of a large amount of data and samples with different characteristics includes clustering which is associated with methods and techniques that have frequently been applied in different fields of researches. A well-known algorithm of clustering is K-means by which the data are divided into K classes based upon a distance criterion. In this study, the K-means method applies for data classification derived from exploration boreholes and surface sampling in the Parkam deposit. The results derived based on the case of...