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Karar Ağaçları ve Genetik Algoritmalar ile İkinci El Otomobil Satış Fiyat Tahmini

Predicting Second-Hand Car Sales Price Using Decision Trees and Genetic Algorithms

Journal Name:

  • Alphanumeric Journal

Publication Year:

  • 2017
DOI: 
10.17093/alphanumeric.323836

Key Words:

Keywords (Original Language):

Author NameUniversity of Author
Abstract (2. Language): 
It is important to predict the sales price of second-hand car for both persons and institutions who are operating in second-hand market. The sales price of cars are affected by many factors which makes predicting difficult. Especially there is no readily available method to determine which factors are affecting the sales price most. The purpose of this study is to predict the sales price of second-hand cars with decision trees. Genetic Algorithm is used to select the most relevant features. For this purpose, 252645 advertisements are scanned fort his study. For each advertisement there are 139 features available. Different models are examined using genetic algorithms with selecting 5, 10, 15 and 20 features. The best predicting performance in the out-of-sample experiment is %65,67. Proposed model can be used as a decision support system for those operating in second-hand car market.
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Abstract (Original Language): 
İkinci el araçların satış fiyatlarının önceden tahmin edilmesi, ikinci el piyasada alım satımla ilgilenen kişi ve kurumlar için önem arz etmektedir. Ancak araçların fiyatlarının birçok faktörden etkilenmesi, satış fiyatının tahmin edilmesini zorlaştırmaktadır. Özellikle araçlara ilişkin hesaplanabilen birçok değişken arasında hangilerinin en iyi tahmin performansını sergileyeceğini belirlemeye yönelik hazır bir yöntem mevcut değildir. Bu çalışmanın amacı karar ağaçları ile ikinci el otomobil satış fiyatını tahmin etmektir. Karar ağaçları için değişken seçimi genetik algoritma ile gerçekleştirilmiştir. Bu amaçla Türkiye’de faaliyet gösteren e-ticaret sitelerinden birinde yer alan 252645 adet otomobile ait satış ilanı taranmıştır. Her bir otomobile ilişkin 139 adet değişken mevcuttur. Genetik Algoritmalar yardımıyla sırasıyla 5, 10, 15 ve 20 adet değişkenin seçildiği modeller incelenmiştir. %65.67 ye varan oranda doğru tahmin gerçekleştirilebilmiştir. Önerilen yöntemi, ikinci el piyasada işlem yapan taraflar karar destek sistemi olarak kullanabilirler.
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Özçalıcı Predicting Second-Hand Car Sales Price Using Decision Trees and Genetic Algorithms 114
Alphanumeric Journal
Volume 5, Issue 1, 2017
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