A Real Data-Driven Clustering Approach for Countries Based on Happiness Score

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a grou...

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Veröffentlicht in:	Amfiteatru economic Jg. 23; H. SI 15; S. 1031 - 1045
Hauptverfasser:	Chakraborty, Aditya, Tsokos, Chris P
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bucharest EDITURA ASE 2021 ASE Publishing House The Bucharest University of Economic Studies Bucharest Academy of Economic Studies, Faculty of Commerce Editura ASE
Schlagworte:	Accuracy Algorithms Business Economy / Management Classification Cluster analysis Clustering Clustering Algorithms Data Decision trees Economic Indicators GDP Gross Domestic Product Groups Happiness Industrialized nations Machine learning Machine Learning Classification Algorithms Productivity Research methodology Social indicators Socioeconomic factors Stability Measures Statistical methods Subjective Well Being (SWB) Clustering Algorithms Machine Learning Classification Algorithms Economic Indicators Stability Measures Subjective Well Being (SWB)
ISSN:	1582-9146, 2247-9104, 2247-9104
Online-Zugang:	Volltext
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