Araştırma Makalesi
BibTex RIS Kaynak Göster

Yıl 2025, Cilt: 21 Sayı: 4, 62 - 69, 29.12.2025
https://doi.org/10.18466/cbayarfbe.1622165

Öz

Kaynakça

  • [1]. Mitchell, TM. Machine Learning. McGraw Hill , Maid enhead, United Kingdom, international student edition. 1997; pp. 1-13.
  • [2]. Russell, S, Norvig, P. Artificial Intelligence: A Modern Approach (4th ed.). Pearson Education Limited, United Kingdom. 2020; pp. 853-882
  • [3]. Manning, CD, Raghavan, P, Schütze, H. Introduction to Information Retrieval. Cambridge: Cambridge University Press. 2008; pp. 80-274.
  • [4]. United Nations. International Standard Industrial Classification of All Economic Activities (ISIC), Rev.4. Retrieved from https://unstats.un.org. (accessed at 25.12.2024).
  • [5]. OECD. Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development. OECD Publishing. Retrieved from https://www.oecd.org. (accessed at 25.12.2024).
  • [6]. World Economic Forum. The Future of Jobs Report 2020. Retrieved from https://www.weforum.org. (accessed at 25.12.2024).
  • [7]. Uludağ, O., Gürsoy, A. 2020. On the financial situation analysis with knn and Naive Bayes classification algorithms. Journal of the Institute of Science and Technology; 10(4): 2881-2888. (https://doi.org/10.21597/jist.703004)
  • [8]. Aker, Y., Karavardar, A. 2023. Using machine learning methods in financial distress prediction: sample of small and medium sized enterprises operating in Turkey. Ege Academic Review; 23(2): 145-162. (https://doi.org/10.21121/eab.1027084)
  • [9]. Bishop, CM. Pattern Recognition and Machine Learning. Springer. Berlin. 2006. pp. 20-30.
  • [10]. Hastie, T, Tibshirani, R, Friedman, J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer. California. 2009. pp. 485
  • [11]. Sutton, RS., & Barto, AG. Reinforcement Learning: An Introduction (2nd ed.). MIT Press, Cambridge, Massachusetts. 2018. pp. 1-25.
  • [12]. LeCun, Y, Bengio, Y, Hinton, G.2015. Deep learning. Nature; 521(7553): 436-444.
  • [13]. Zhang, H. The Optimality of Naive Bayes. Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, USA, 2004, pp 312–317.
  • [14]. Murphy, KP. Machine Learning: A Probabilistic Perspective. MIT Press. Cambridge, Massachusetts. 2012. pp. 1-31.
  • [15]. McCallum, A, & Nigam, KA. Comparison of Event Models for Naive Bayes Text Classification. AAAI-98 Workshop on Learning for Text Categorization, Madison, Wisconsin, 1998, pp 41-48.
  • [16]. Rennie, JDM, Shih, L, Teevan, J, & Karger, DR. Tackling the Poor Assumptions of Naive Bayes Text Classifiers. Proceedings of the 20th International Conference on Machine Learning (ICML-03), Washington, DC USA 2003, pp 616–623.

Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm

Yıl 2025, Cilt: 21 Sayı: 4, 62 - 69, 29.12.2025
https://doi.org/10.18466/cbayarfbe.1622165

Öz

Machine learning is a cornerstone of data science, enabling the analysis and prediction of complex data patterns. Among various algorithms, Naive Bayes is a popular probabilistic classifier based on Bayes' theorem, assuming strong independence among features. Its efficiency in handling large datasets, coupled with ease of implementation, makes it a valuable tool in data science workflows. The purpose of this study is to illustrate the research and development trends of Turkish business enterprises based on unit of measure (national currency or US dollars) and price basis measurements by the Naive Bayes algorithm. The result of classifying shows that economic activities show varied preferences for currency and price bases: agriculture, forestry, and fishing, construction, and sewerage, waste management, and remediation activities are split equally between national and US dollar currencies and price types. Manufacturing favors current prices; mining and quarrying prefer national currency and current prices, while services lean towards the US dollar and current prices. Business enterprises with all economic activities prioritize the national currency (67%) and constant prices (67%).

Kaynakça

  • [1]. Mitchell, TM. Machine Learning. McGraw Hill , Maid enhead, United Kingdom, international student edition. 1997; pp. 1-13.
  • [2]. Russell, S, Norvig, P. Artificial Intelligence: A Modern Approach (4th ed.). Pearson Education Limited, United Kingdom. 2020; pp. 853-882
  • [3]. Manning, CD, Raghavan, P, Schütze, H. Introduction to Information Retrieval. Cambridge: Cambridge University Press. 2008; pp. 80-274.
  • [4]. United Nations. International Standard Industrial Classification of All Economic Activities (ISIC), Rev.4. Retrieved from https://unstats.un.org. (accessed at 25.12.2024).
  • [5]. OECD. Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development. OECD Publishing. Retrieved from https://www.oecd.org. (accessed at 25.12.2024).
  • [6]. World Economic Forum. The Future of Jobs Report 2020. Retrieved from https://www.weforum.org. (accessed at 25.12.2024).
  • [7]. Uludağ, O., Gürsoy, A. 2020. On the financial situation analysis with knn and Naive Bayes classification algorithms. Journal of the Institute of Science and Technology; 10(4): 2881-2888. (https://doi.org/10.21597/jist.703004)
  • [8]. Aker, Y., Karavardar, A. 2023. Using machine learning methods in financial distress prediction: sample of small and medium sized enterprises operating in Turkey. Ege Academic Review; 23(2): 145-162. (https://doi.org/10.21121/eab.1027084)
  • [9]. Bishop, CM. Pattern Recognition and Machine Learning. Springer. Berlin. 2006. pp. 20-30.
  • [10]. Hastie, T, Tibshirani, R, Friedman, J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer. California. 2009. pp. 485
  • [11]. Sutton, RS., & Barto, AG. Reinforcement Learning: An Introduction (2nd ed.). MIT Press, Cambridge, Massachusetts. 2018. pp. 1-25.
  • [12]. LeCun, Y, Bengio, Y, Hinton, G.2015. Deep learning. Nature; 521(7553): 436-444.
  • [13]. Zhang, H. The Optimality of Naive Bayes. Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference, USA, 2004, pp 312–317.
  • [14]. Murphy, KP. Machine Learning: A Probabilistic Perspective. MIT Press. Cambridge, Massachusetts. 2012. pp. 1-31.
  • [15]. McCallum, A, & Nigam, KA. Comparison of Event Models for Naive Bayes Text Classification. AAAI-98 Workshop on Learning for Text Categorization, Madison, Wisconsin, 1998, pp 41-48.
  • [16]. Rennie, JDM, Shih, L, Teevan, J, & Karger, DR. Tackling the Poor Assumptions of Naive Bayes Text Classifiers. Proceedings of the 20th International Conference on Machine Learning (ICML-03), Washington, DC USA 2003, pp 616–623.
Toplam 16 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İstatistiksel Veri Bilimi
Bölüm Araştırma Makalesi
Yazarlar

Esin Avcı 0000-0002-9173-0142

Gönderilme Tarihi 17 Ocak 2025
Kabul Tarihi 6 Haziran 2025
Yayımlanma Tarihi 29 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 21 Sayı: 4

Kaynak Göster

APA Avcı, E. (2025). Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm. Celal Bayar University Journal of Science, 21(4), 62-69. https://doi.org/10.18466/cbayarfbe.1622165
AMA Avcı E. Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm. Celal Bayar University Journal of Science. Aralık 2025;21(4):62-69. doi:10.18466/cbayarfbe.1622165
Chicago Avcı, Esin. “Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm”. Celal Bayar University Journal of Science 21, sy. 4 (Aralık 2025): 62-69. https://doi.org/10.18466/cbayarfbe.1622165.
EndNote Avcı E (01 Aralık 2025) Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm. Celal Bayar University Journal of Science 21 4 62–69.
IEEE E. Avcı, “Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm”, Celal Bayar University Journal of Science, c. 21, sy. 4, ss. 62–69, 2025, doi: 10.18466/cbayarfbe.1622165.
ISNAD Avcı, Esin. “Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm”. Celal Bayar University Journal of Science 21/4 (Aralık2025), 62-69. https://doi.org/10.18466/cbayarfbe.1622165.
JAMA Avcı E. Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm. Celal Bayar University Journal of Science. 2025;21:62–69.
MLA Avcı, Esin. “Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm”. Celal Bayar University Journal of Science, c. 21, sy. 4, 2025, ss. 62-69, doi:10.18466/cbayarfbe.1622165.
Vancouver Avcı E. Revealing the Tendency of Analytical Business Enterprises Toward Currency and Prices Via the Naive Bayes Algorithm. Celal Bayar University Journal of Science. 2025;21(4):62-9.