A real data-driven clustering approach for countries based on happiness score
Year of publication: |
2021
|
---|---|
Authors: | Chakraborty, Aditya ; Tsokos, Chris P. |
Published in: |
Amfiteatru Economic Journal. - ISSN 2247-9104. - Vol. 23.2021, Special Issue No. 15, p. 1031-1045
|
Publisher: |
Bucharest : The Bucharest University of Economic Studies |
Subject: | Clustering Algorithms | Subjective Well Being (SWB) | Stability Measures | Machine Learning Classification Algorithms | Economic Indicators |
Type of publication: | Article |
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Type of publication (narrower categories): | Article |
Language: | English |
Other identifiers: | 10.24818/EA/2021/S15/1031 [DOI] 179563068X [GVK] hdl:10419/281616 [Handle] |
Classification: | C00 - Mathematical and Quantitative Methods. General ; C02 - Mathematical Methods ; C19 - Econometric and Statistical Methods: General. Other ; C40 - Econometric and Statistical Methods: Special Topics. General ; C49 - Econometric and Statistical Methods: Special Topics. Other ; C65 - Miscellaneous Mathematical Tools ; y91 ; Y10 - Data: Tables and Charts |
Source: |
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A real data-driven clustering approach for countries based on happiness score
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A real data-driven clustering approach for countries based on happiness score
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