AN INVESTIGATION OF HOTEL BOOKING CANCELLATION USING MACHINE LEARNING APPROACHES IN PYTHON

Aug 5, 2026

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Hotel booking cancellation analysis focuses on building an efficient bookings management system for the hotel industry. The study uses 119,390 observations and 32 variables from two hotels, one in a city and one in a resort. Multiple machine learning methods implemented in Python on a Jupyter notebook dataset are applied to identify drivers of cancellations. The work is motivated by the COVID-19 pandemic’s impact and aims to reduce canceled reservations, helping organizations gain competitive advantage while accounting for demographic and seasonal differences.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages63

Reading Time2 h 39 min

AccessFree to download

Introduction

Methodology/Analysis

Variables

Pre-munging/processing of the data

Descriptive statistics

Feature engineering

Label encoding

Data reduction and selection

Correlation matrix and heatmap

Feature selection and data normalization

Train Test Split

K-Nearest Neighbors (KNN)

Logistic Regression

Discussion

Possible Improvements

References

St. John's University St. John's Scholar Theses and Dissertations 2023 AN INVESTIGATION OF HOTEL BOOKING CANCELLATION USING MACHINE LEARNING APPROACHES IN PYTHON Diogo Marques Follow this and additional works at: [https://scholar.stjohns.edu/theses_dissertations](https://scholar.stjohns.edu/theses_dissertations) AN INVESTIGATION OF HOTEL BOOKING CANCELLATION USING MACHINE LEARNING APPROACHES IN PYTHON A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE to the faculty of the DEPARTMENT OF BUSINESS ANALYTICS AND INFORMATION SYSTEMS of THE PETER J. TOBIN COLLEGE OF BUSINESS at ST. JOHN'S UNIVERSITY New York by Diogo Marques Date Submitted 8/25/2023 Diogo Marques Date Submitted 8/25/2023 Dr. Yanni Ping © Copyright by Diogo Marques 2023 All Rights Reserved ABSTRACT AN INVESTIGATION OF HOTEL BOOKING CANCELLATION USING MACHINE LEARNING APPROACHES IN PYTHON Diogo Marques This work will be focusing on the hotel industry and how to develop an efficient bookings management system. There are 119,390 observations and 32 variables provided by two distinct hotels, one located in a city and the other in a resort. Multiple machine learning and Python techniques will be used on a jupyter notebook Python file. This work is extremely useful since the recent pandemic (Covid-19) has greatly impacted the hotel industry. Reducing the number of canceled reservations system will possibly allow the organizations to gain a competitive advantage. However, the most adequate booking system for a hotel might not be for any other. Thus, being something that changes both demographically and seasonally. DEDICATION This work is dedicated to my parents, who have incessantly prioritized myself and my values over any other matters. I hope that their power of will and sense of justice is going to always guide me through the tougher challenges I will face and lead me to the best decision-making to overcome them, whilst keeping the utmost respect by all of those who surround me. I also take this opportunity to thank those that are or were closer to me and have contributed to shaping me into the person I am today. ACKNOWLEDGEMENTS I would like to thank my thesis mentor Dr. Yanni Ping for everything she has taught me during our time at St. John’s University. There are truly no words to describe her dedication to my learning, and her support that was essential for me to be able to conclude this work. Her kindness and empathy will forever mark me in a very special way. Also, I am grateful to dean Susan McCall and academic supervisor Ray Howell, who have majorly contributed to successfully conclude my master’s degree. TABLE OF CONTENTS DEDICATION .................................................................................................................... ii ACKNOWLEDGEMENTS ............................................................................................... iii LIST OF TABLES .............................................................................................................. v [LIST OF FIGURES ........................................................................................................... vi](LIST OF FIGURES ........................................................................................................... vi) [INTRODUCTION ...............................](INTRODUCTION ...............................)............................................................................... 1 METHODOLOGY/ANALYSIS......................................................................................... 4 Variables ......................................................................................................................... 4 Pre-munging/processing of the data................................................................................ 7 Descriptive statistics ............................

FAQs

What data and scope does the study use for hotel booking cancellations?

The study uses 119,390 observations and 32 variables collected from two hotels: one located in a city and one in a resort.

Which tools and techniques are applied in the analysis?

Multiple machine learning approaches are implemented using Python in a Jupyter notebook workflow, including preprocessing, feature engineering, normalization, and model training.

Why is reducing booking cancellations important according to the document?

Reducing canceled reservations can help organizations gain a competitive advantage, especially given the significant impact of the COVID-19 pandemic on the hotel industry.

Aug 5, 2026

Upload by Finn