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An Investigation of Hotel Booking Cancellation Using Machine Learning Approaches in Python.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
An Investigation of Hotel Booking Cancellation Using Machine Learning Approaches in Python./
作者:
Marques, Diogo.
面頁冊數:
1 online resource (63 pages)
附註:
Source: Masters Abstracts International, Volume: 85-03.
Contained By:
Masters Abstracts International85-03.
標題:
Statistics. -
電子資源:
click for full text (PQDT)
ISBN:
9798380325080
An Investigation of Hotel Booking Cancellation Using Machine Learning Approaches in Python.
Marques, Diogo.
An Investigation of Hotel Booking Cancellation Using Machine Learning Approaches in Python.
- 1 online resource (63 pages)
Source: Masters Abstracts International, Volume: 85-03.
Thesis (M.S.)--St. John's University (New York), 2023.
Includes bibliographical references
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.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024
Mode of access: World Wide Web
ISBN: 9798380325080Subjects--Topical Terms:
556824
Statistics.
Subjects--Index Terms:
Machine learningIndex Terms--Genre/Form:
554714
Electronic books.
An Investigation of Hotel Booking Cancellation Using Machine Learning Approaches in Python.
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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.
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click for full text (PQDT)
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