Determining the best estimation model with tree-based machine learning methods: Implementation on customer spendings for e-commerce websites

Yalçın, MehmetBağdatlı Kalkan, Seda2023-02-232023-02-232022https://hdl.handle.net/11467/6307https://doi.org/10.17654/0972361722029Individuals who can easily access Internet have turned to online shopping instead of shopping in physical stores as a result of the development of technology. Individuals’ tendency for online shopping has improved the e-commerce sector. Factors such as ability to realize global sales, reduction in physical store expenses, ability to realize 24/7 sales, online and low-cost stock tracking make e-commerce important. Since they use Internet channels in purchasing, the mobility of the customers is also monitored and the behavior of the customers is reflected as data. Thus, the number of studies that predicts the purchasing behavior of customers increases along with prediction models.eninfo:eu-repo/semantics/openAccesstree-based models, e-commerce, machine learning, ensemble learningDetermining the best estimation model with tree-based machine learning methods: Implementation on customer spendings for e-commerce websitesArticle7591109N/AWOS:00088675310000610.17654/0972361722029