Abstract
The literature presents many methods for partitioning of data set, and is difficult choose which is the most suitable, since the various combinations of methods based on different measures of dissimilarity can lead to different patterns of grouping and false interpretations. Nevertheless, little effort has been expended in evaluating these methods empirically using an archaeological data set. In this way, the objective of this work is make a comparative study of the different cluster analysis methods and identify which is the most appropriate. For this, the study was carried out using a data set of 45 samples of ceramic fragments, analyzed by instrumental neutron activation analysis (INAA). The methods used for this study were: Single linkage, Complete linkage, Average linkage, Centroid and Ward. The validation was done using the cophenetic correlation coefficient and comparing these values the average linkage method obtained better results. A script of the statistical program R with some functions was created to obtain the cophenetic correlation. By means of these values was possible to choose the most appropriate method to be used in the data set.
Highlights
In the last years, cluster analysis has increasing your emphasis in multivariate data analysis
For distance Mahalanobis, the groups formed are not well-defined and presented samples mixtures from different sites, which leads to false interpretations
Several clustering methods types are found in the literature, with the researcher deciding which is most suitable for their purpose, since the various methods combinations based on different dissimilarity measures can lead to different data set cluster
Summary
Cluster analysis has increasing your emphasis in multivariate data analysis. Clustering techniques are tools where the application and interpretation are subjective, depending on the experience and user perspicacity [1]. Different clustering methods produce different results when applied to the same data [2]. Little effort has been expended in evaluating these methods empirically using an archaeological data set. In archaeological studies several analytical techniques are used to study the chemical and mineralogical composition of many archaeological materials with the objective of to find yours origin, generating a large data set. The multivariate statistical methods become indispensable for the results interpretation
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