Identification of the element dispersion patterns and relating them to the geochemical anomalies is one of the exploration tools, especially in the semi-detailed and detailed phases. Methods that can simultaneously analyze samples and elements are recommended for this purpose. In this paper, two methods namely, correspondence cluster analysis (CCA) and density-based clustering algorithm (DENCLUE) and the geochemical data of Khoynaroud region have been used. Clustering of 165 soil samples, along with the results of the 7 elements analysis associated to the porphyry copper-gold mineralization, namely As, Au, Cu, Hg, Pb, S and Zn, shows that four A, B, C and D areas are visible with mineralization potential in the study area. In CCA method, the data are divided into 6 clusters. These clusters contain S with 57 samples, 61 samples, Pb with 16 samples, Cu with 8 samples, As with 7 samples and Au, Hg and Zn with 17 samples, respectively. While in DENCLUE method include 5 clusters in the form of S with 66 samples, 43 samples, Pb and Zn with 38 samples, Au and Cu with 10 samples and As and Hg with 8 samples, respectively. Part C2 of area C and part D2 of area D are proposed as the best areas with the possibility of porphyry mineralization and as well as area A with the possibility of hydrothermal vein mineralization. Area B and part D1 with the possibility of vein mineralization and the need for additional exploration are also likely to be the next proposals. The results also show the better clustering of the elements, better adaptation of the proposed areas for mineralization with multi-element geochemical anomalies and geological conditions of the study area are the advantages of DENCLUE algorithm. Therefore, this algorithm can be used to relate the element dispersion pattern with their geochemical anomaly.