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Journals / Veri Bilimi / 2018 / Cilt: 1 - Sayı: 1

Predicting Hotel Reservation Cancellation by Using Machine Learning Methods

Otel Rezervasyon İptallerinin Makine Öğrenmesi Yöntemleri ile Tahmin Edilmesi

Mehmet BOZ
Erokan CANBAZOĞLU
Zeki ÖZEN
Sevinç GÜLSEÇEN
Pages
7–14
Publication Date
2018-12-25
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The best result was obtained from C4.5 decision tree algorithm with 73% accuracy.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In order to maximize profit for hotels, occupancy rates must be high.
📊
Key Findings & Data:In this study, the hotel reservation data set consisting of 38,826 records of 5 different hotels were analyzed by machine learning algorithms to estimate the cancellation of future bookings of hotels.
💡
Conclusion & Impact:The best result was obtained from C4.5 decision tree algorithm with 73% accuracy.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:otel rezervasyon iptali · makine öğrenmesi · danışmanlı öğrenme

Abstract

In order to maximize profit for hotels, occupancy rates must be high. For this reason, hotels should allocate a limited number of their rooms to the right customer at the right time using reservation systems software. However, reservations may be cancelled by the customer for various reasons. Cancellations may result for hotels in loss of income if the right policies are not processed. For this reason, it is very important to estimate reservation cancellations. In this study, the hotel reservation data set consisting of 38,826 records of 5 different hotels were analyzed by machine learning algorithms to estimate the cancellation of future bookings of hotels. In this context, 4 different models were formed in this study by using Random Forest (RF), Support Vector Machines (SVM), k-Nearest Neighbor (kNN) and Decision Tree (C4.5) algorithms and then, performance comparisons were made among these models. The best result was obtained from C4.5 decision tree algorithm with 73% accuracy.

Özet

Konaklama hizmeti veren otellerin maksimum kâr elde edebilmesi için doluluk oranlarının yüksek olması gerekmektedir. Bu sebeple oteller rezervasyon sistemleri aracılığıyla sınırlı sayıdaki odalarını doğru zamanda, doğru müşteriye tahsis etmelidir. Ancak rezervasyonlar çeşitli nedenlerle müşteri tarafından iptal edilebilmektedir. Oteller açısından iptal edilen rezervasyonlar doğru politikalar izlenmezse gelir kaybına neden olabilmektedir. Bu sebeple iptallerin önceden tahmin edilmesi büyük önem taşımaktadır. Bu çalışmada, makine öğrenmesi teknikleriyle 5 farklı otele ait toplam 38.826 kayıttan oluşan hotel rezervasyon verisi kullanılarak otellerin gelecekteki rezervasyonlarının iptal durumları tahmin edilmeye çalışılmıştır. Çalışmada sınıflandırma algoritmalarından Random Forest Algoritması (RF), Destek Vektör Makineleri (SVM), k-En Yakın Komşu (kNN) ve Karar Ağacı (C4.5) algoritmaları kullanılarak 4 farklı model oluşturulmuş ve modellerin performans karşılaştırmaları yapılmıştır. En iyi sonuç %73 doğruluk oranı ile C4.5 karar ağacı algoritmasından elde edilmiştir.

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Cite This Article

BOZ, M., CANBAZOĞLU, E., ÖZEN, Z., GÜLSEÇEN, S. (2018). Predicting Hotel Reservation Cancellation by Using Machine Learning Methods. Veri Bilimi, Cilt: 1 - Sayı: 1, 7–14. https://ajindex.com/articles/821885

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