Process of machine learning methods

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dc.authorscopusid58576580300
dc.contributor.authorKoçyiğit, Hülya
dc.date.accessioned2024-01-22T12:22:47Z
dc.date.available2024-01-22T12:22:47Z
dc.date.issued2023
dc.departmentKMÜ, Eğitim Fakültesi, Matematik ve Fen Bilimleri Eğitimi Bölümüen_US
dc.description.abstractThe 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.en_US
dc.identifier.citationKoçyiğit, 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.ch001en_US
dc.identifier.doi10.4018/978-1-6684-8386-2.ch001
dc.identifier.endpage38en_US
dc.identifier.isbn9781668483886
dc.identifier.isbn1668483866
dc.identifier.isbn9781668483862
dc.identifier.scopus2-s2.0-85171235237
dc.identifier.scopusqualityN/A
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.4018/978-1-6684-8386-2.ch001
dc.identifier.urihttps://hdl.handle.net/11492/8142
dc.indekslendigikaynakScopus
dc.institutionauthorKoçyiğit, Hülya
dc.language.isoen
dc.publisherIGI Globalen_US
dc.relation.journalAdvancement in Business Analytics Tools for Higher Financial Performanceen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleProcess of machine learning methodsen_US
dc.typeBook Part

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EğitimFakültesi, Matematik ve Fen Bilimleri Eğitimi Bölümü, Kitap ve Kitap Bölümleri Koleksiyonu