Özet:

Classification can be defined as the process of examining the structures of the data observed on any subject and grouping the data according to similar groups, contents and some characteristics we have determined. Thus, it will be easier to evaluate and interpret the observations in similar groups according to the research objectives. Cluster analysis is one of the most frequently used methods in classification studies. Cluster analysis is a multivariate statistical method that aims to classify data without natural groups into a limited number of groups or clusters. In the Gray Relational Clustering method, since the clusters consist of objects grouped according to a certain rule, the clusters have homogeneity and it is a method that can distinguish objects within itself without the need for recalculation. In addition, since the number of clusters can be determined after clustering is performed, not before the analysis, it can offer an alternative approach to other commonly used clustering algorithms. In this study, it is aimed to classify the provinces in Turkiye by using gray clustering analysis with the help of socio-economic data. Gray relational coefficient matrices were first created with the data obtained from the Turkish Statistical Institute and then clustering analysis was performed to determine the distribution of provinces according to socio-economic data. Analyses were also conducted separately for the data categories given under sub-headings such as education, agriculture and employment, and with this it is aimed to determine the socio-economic map of Turkiye.

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