Process of machine learning methods
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Tarih
2023
Yazarlar
Dergi Başlığı
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Cilt Başlığı
Yayıncı
IGI Global
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The field of machine learning (ML) has grown to be a prominent subject within developed businesses while aiming to implement data-driven techniques to better day-to-day business activities. The reader is introduced to the most popular learning models in this chapter. Although unsupervised learning, reinforcement learning, and semi-supervised learning are incredibly important, the authors won 't go into further detail about them here. This section will go into great length about supervised learning environments. The authorspropose the following as a summary of the contributions to this chapter: Emphasizing some of the earlier works of literature that tackled these problems and discussing their limitations. In order to do so, the authorspropose to review the regression family (i.e., simple regression and multiple linear regression) and decision tree family (i.e., CART, ID3, C4.5, chi-squared automatic interaction detection (CHAID), bagging and boosting). Examining the function and promise of ML techniques to resolve dilemmas and present potential implementation strategies. © 2023, IGI Global. All rights reserved.
Açıklama
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WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
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Künye
Koçyiğit, H. (2023). Process of machine learning methods. In R. Gharoie Ahangar & M. Napier (Eds.), Advancement in Business Analytics Tools for Higher Financial Performance (pp. 1-38). IGI Global. https://doi.org/10.4018/978-1-6684-8386-2.ch001
