Acta Infologica

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DOI :10.26650/acin.1251650   IUP :10.26650/acin.1251650    Full Text (PDF)

Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning

Merve Doğruel, Selin Soner Kara

Today, the concept of happiness is a frequently researched subject in the fields of economy, medicine, and social and political fields, aswell as psychology. It has been an important research area for everyone, from policymakers to companies, to determine the factors affecting happiness. With machine learning algorithms, it is possible to make classifications with very high accuracy. The aim of this study is to use tree-based machine learning algorithms to classify the happiness scores of countries. In order to accomplish this, data from the World Happiness Index published in 2022 were used. On these data, tree-based algorithms CART, tree-based ensemble algorithms Bagging, and Random Forest were used. The test data of the model were obtained with 85% precision, recall, and F1 metrics, which were calculated using Bagging and Random Forest algorithms. The outcomes of the models obtained during the study were interpreted.

Keywords: Machine learning, World Happiness Index, Ensemble learning
DOI :10.26650/acin.1251650   IUP :10.26650/acin.1251650    Full Text (PDF)

Makine Öğrenmesinde Ağaç Tabanlı Algoritmalarla Ülkelerin Mutluluk Sınıfının Belirlenmesi

Merve Doğruel, Selin Soner Kara

Mutluluk kavramı günümüzde psikoloji alanı dışında ekonomi, tıp, sosyal ve politik alanlarda da sıklıkla araştırılan bir konu haline gelmiştir. Mutluluğu etkileyenfaktörlerin belirlenmesi, politika yapıcılardan işletmelere kadar önemli bir araştırma alanı olmuştur. Makine öğrenmesi algoritmaları ile yüksek doğrulukta sınıflandırmalar çalışmaları yapmak mümkündür. Bu çalışmada, ağaç tabanlı makine öğrenmesi algoritmaları kullanılarak ülkelerin mutluluk puanlarının sınıflandırılması amaçlanmaktadır. Bu amaçla 2022 yılında yayınlanan Dünya Mutluluk Endeksi’nden alınan veriler kullanılmıştır. Bu veriler üzerinde ağaç tabanlı algoritmalar SRT, ağaç tabanlı topluluk algoritmaları torbalama ve rastgele orman kullanılmıştır. Torbalama ve rastgele orman algoritmaları ile elde edilen modelin test verilerinde %85 kesinlik, duyarlılık ve F1 metrikleri hesaplanmıştır. Çalışmada elde edilen bu modellerin sonuçları yorumlanmıştır.

Keywords: Makine öğrenmesi, Dünya Mutluluk Endeksi, Topluluk öğrenmesi

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APA

Doğruel, M., & Soner Kara, S. (2023). Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning. Acta Infologica, 7(2), 243-252. https://doi.org/10.26650/acin.1251650


AMA

Doğruel M, Soner Kara S. Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning. Acta Infologica. 2023;7(2):243-252. https://doi.org/10.26650/acin.1251650


ABNT

Doğruel, M.; Soner Kara, S. Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning. Acta Infologica, [Publisher Location], v. 7, n. 2, p. 243-252, 2023.


Chicago: Author-Date Style

Doğruel, Merve, and Selin Soner Kara. 2023. “Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning.” Acta Infologica 7, no. 2: 243-252. https://doi.org/10.26650/acin.1251650


Chicago: Humanities Style

Doğruel, Merve, and Selin Soner Kara. “Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning.” Acta Infologica 7, no. 2 (Apr. 2024): 243-252. https://doi.org/10.26650/acin.1251650


Harvard: Australian Style

Doğruel, M & Soner Kara, S 2023, 'Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning', Acta Infologica, vol. 7, no. 2, pp. 243-252, viewed 28 Apr. 2024, https://doi.org/10.26650/acin.1251650


Harvard: Author-Date Style

Doğruel, M. and Soner Kara, S. (2023) ‘Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning’, Acta Infologica, 7(2), pp. 243-252. https://doi.org/10.26650/acin.1251650 (28 Apr. 2024).


MLA

Doğruel, Merve, and Selin Soner Kara. “Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning.” Acta Infologica, vol. 7, no. 2, 2023, pp. 243-252. [Database Container], https://doi.org/10.26650/acin.1251650


Vancouver

Doğruel M, Soner Kara S. Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning. Acta Infologica [Internet]. 28 Apr. 2024 [cited 28 Apr. 2024];7(2):243-252. Available from: https://doi.org/10.26650/acin.1251650 doi: 10.26650/acin.1251650


ISNAD

Doğruel, Merve - Soner Kara, Selin. “Determining the Happiness Class of Countries with Tree-Based Algorithms in Machine Learning”. Acta Infologica 7/2 (Apr. 2024): 243-252. https://doi.org/10.26650/acin.1251650



TIMELINE


Submitted15.02.2023
Accepted01.08.2023
Published Online24.08.2023

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