Saeid Esmaeiloghli, SEYED HASSAN TABATABAEI, HARONI HOOSHANG ASADI
Volume 9 Issue 18 Pages 61-76 Publisher JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING
Description This paper presents an innovative approach for calculating the correct number of groups in the geochemical data sets. The proposed method reduces the uncertainty of traditional methods that is often based on expert knowledge or application of a unique index. On the basis of separation and compactness of clusters، several pattern recognition indices (thirty indices) are used to produce the response distribution. Then، the optimal solution is concluded from the possible answers which are selected on the basis of the maximum frequency of distribution. This process has been implemented on a simulated data set which ultimately has been managed to properly identify the true number of artificial clusters. It has also been applied to a real geochemical data set، and consequently، three clusters are estimated as the optimum group numbers in the data set. The three groups resulted from data clustering are fully correlated with the geological and geochemical evidences in the study area. Introduction: Partitioning of the heterogeneous data set into homogeneous subsets is an important goal of geochemical data processing which clustering tools are usually used to achieve this goal. Nevertheless، the most important practical challenge in this regard is an estimation of the actual number of underlying groups in the data set. This is traditionally related to descriptive geochemical information، expert knowledge، and unique statistical index. Due to the instability and uncertainty of the mentioned approaches، we recommend solving the problem by implementing the whole range of indices، creating a distribution of possible responses and consequently …