International Journal of Computational and Experimental Science and Engineering

Yazarlar: Billur ECER, Ahmet AKTAŞ

Konular:Mühendislik

DOI:10.22399/ijcesen.416611

Anahtar Kelimeler:Data mining,Clustering,Healthcare indicators,EU countries

Özet: Health is always considered as one of the most important issues related to human being. Due to this importance, governments should primarily provide the best healthcare services to their citizens. Some indicators can show the quality of healthcare services in the country. However, one country can have a higher value of one indicator and can have a lower value of another. Thus, countries can be categorized in terms of quality of healthcare services. Clustering is a useful tool for comparing countries and defining the similar countries in terms of healthcare services. In this study, 28 European Union (EU) countries were evaluated on 14 health factors and the number of clusters was determined by the generally accepted rule of thumb. To cluster countries, k-means clustering method is run in WEKA software for two cluster numbers and four different initial solution approaches. The resulting clusters were evaluated according to the Spearman rank correlation coefficient using the order of the GDP per capita values of the countries in each cluster. It seems using four clusters with Canopy initial solution approach is the most appropriate way of clustering.

---