@misc{Pełka_Marcin_Analysis_2019,
 author={Pełka, Marcin},
 identifier={DOI: 10.15611/eada.2019.3.02},
 year={2019},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Econometrics = Ekonometria, 2019, Vol. 23, No. 3, s. 15-25},
 language={eng},
 abstract={The results of happiness analysis are presented in the form of a World Happiness Report that covers 156 countries and 17 different indicators. In the article model-based clustering ensemble is built to determine what selected European countries have similar patterns of happiness. The results are analyzed using multidimensional scaling and a decision tree to find out what factors determine cluster memberships. In the empirical part, three clusters were detected The first contains countries: Austria, Denmark, Finland, Germany, Ireland, Luxembourg, the Netherlands, Norway, Sweden, Switzerland and the United Kingdom. They have the highest values for all the variables, except the negative affect. The second cluster contains seven countries: Bulgaria, Estonia, Hungary, Lithuania, Poland, Romania and Slovakia. This cluster is also the most homogeneous one. The third cluster contains eight countries: Cyprus, the Czech Republic, France, Greece, Italy, Portugal, Slovenia and Spain},
 title={Analysis of happiness in EU countries using the multi-model classification based on models of symbolic data},
 type={artykuł},
 keywords={happiness, European Union, symbolic data analysis, ensemble clustering, zadowolenie, Unia Europejska, analiza danych symbolicznych, klasyfikacja wielomodelowa},
}