Computer-Aided Cluster Analysis as a Rapid Method Assisting Mineral Identification: ABSTRACT

Abstract

Cluster analysis is one of the multivariate statistical methods that measure the similarity between objects. Aided by a microcomputer, cluster analysis offers rapid results that can lead to mineral identification based on the chemical composition of the minerals. In the process of cluster analysis, the chemical composition of the unknown minerals is either stored into a data file during an on-line quantitative analysis (e.g., electron microprobe analysis), or manually input to the data file. The data of the unknown minerals are respectively compared with an existing identification data matrix that consists of the chemical composition of related reference minerals. The unknown minerals can then be identified with the reference minerals by the closest similarity (e.g., highest correlation coefficient or lowest distance coefficient) in the dendrogram. By using the concentrations of major and minor elements as the variables, quantitative data obtained from some electron microprobe analyses have been tested and approximately 80% of unknown minerals are accurately identified.