An application for the classification of egg quality and haugh unit based on characteristic egg features using machine learning models
Yazarlar (2)
Doç. Dr. Eftal ŞEHİRLİ Karabük Üniversitesi, Türkiye
Arş. Gör. Kübra ARSLAN Karabük Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Expert Systems with Applications (Q1) | ||
| Dergi ISSN | 0957-4174 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 11-2022 |
| Cilt / Sayı / Sayfa | 205 / 1 / 1–6 | DOI | 10.1016/j.eswa.2022.117692 |
| Makale Linki | http://dx.doi.org/10.1016/j.eswa.2022.117692 | ||
| UAK Araştırma Alanları |
Makine Öğrenmesi
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| Özet |
| With the increase in the world population, the nutritional needs of people have been increased. The demand for eggs which is one of the most important food sources has been increased over years. Therefore, it is very important to inform people about egg quality in order to be prepared for adverse situations such as substitution, mislabeling, and fraud. In this study, it is aimed to specify egg quality without using haugh unit (HU). Besides, another aim is to find how much information HU carries about the specification of egg quality. A dataset including 20 features related to eggs taken from 438 chickens created by Poultry Research Institute (PRI) has been analyzed. An application that can classify egg qualities as very good and excellent using machine learning (ML) models like decision tree (DT), linear discriminant analysis (LDA), logistic regression (LR), naïve bayes (NB), support vector machines (SVM), K-nearest … |
| Anahtar Kelimeler |
| Classification | Egg quality | Haugh unit | Machine learning |
Science Direct
An application for the classification of egg quality and haugh unit based on characteristic egg features using machine learning models
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 25 |
| Scopus | 26 |
| Google Scholar | 44 |