An Approach for Airfare Prices Analysis with Penalized Regression Methods

Year 2021, Volume: 4 Issue: 2, 57 - 61, 19.08.2021

Selim Buyrukoğlu , Yıldıran Yılmaz

Abstract

At present, the number of passengers preferring to use the airline is increasing with each passing day. Thus, correctly analysing the airfare prices is essential to raise awareness of passengers. Some researchers have applied different kinds of Machine Learning (ML) algorithms to predict the airfare prices. However, to the best of our knowledge, penalized regression methods have not been used to analyse the airfare prices. Ridge, Lasso and Elastic Net regressions are penalized regression methods. The dataset used in this study consists of 1814 one-way flights from Greece to Germany. The developed Ridge, Lasso and Elastic Net methods were achieved to provide convincing results (MSE) for airfare prices analysis (Ridge:160103, Lasso:159280, Elastic Net:174203). The results and findings reveal that the proposed Lasso method is potentially better than the others in the analysis of datasets consisting one-way of flights.

Keywords

Airfare Price, Analysis Model, Penalised Regression Methods

An Approach for Airfare Prices Analysis with Penalized Regression Methods

Abstract

Günümüzde havayolu kullanmayı tercih eden yolcu sayısı her geçen gün artmaktadır. Bu nedenle uçak bileti fiyatlarının doğru analiz edilmesi yolcuların bilinçlendirilmesi açısından önemlidir. Bazı araştırmacılar, uçak bileti fiyatlarını analiz etmek için farklı türden Makine Öğrenimi (ML) modelleri uyguladılar. Ancak, bildiğimiz kadarıyla, uçak bileti fiyatlarını analiz etmek için cezalı regresyon yöntemleri uygulanmadı. Ridge, Lasso ve Elastic Net regresyonları cezalandırılmış regresyon yöntemleridir. Bu çalışmada kullanılan veri seti Yunanistan'dan Almanya'ya 1814 tek yönlü uçuştan oluşmaktadır. Geliştirilen Ridge, Lasso ve Elastic Net yöntemleri, uçak bileti fiyatları analizi (Ridge:160103, Lasso:159280, Elastic Net:174203) için ikna edici sonuçlar (MSE) elde etmiştir. Sonuçlar ve bulgular, önerilen Lasso yönteminin tek yönlü uçuşlardan oluşan veri setlerinin analizinde potansiyel olarak diğerlerinden daha iyi olduğunu ortaya koymaktadır.

Keywords

Uçak Bileti Fiyatı, Analiz Modeli, Cezalandırılmış Regresyon Yöntemleri

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