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predict the customer who likely to cancel the online hotel reservation

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Nas-virat/Hotel_reservation

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Hotel_reservation

Kaggle

https://www.kaggle.com/code/nasvirat/hotel-reservation-classification

Context

The online hotel reservation channels have dramatically changed booking possibilities and customers’ behavior. A significant number of hotel reservations are called-off due to cancellations or no-shows. The typical reasons for cancellations include change of plans, scheduling conflicts, etc. This is often made easier by the option to do so free of charge or preferably at a low cost which is beneficial to hotel guests but it is a less desirable and possibly revenue-diminishing factor for hotels to deal with.

Data Dictionary

  • Booking_ID: unique identifier of each booking
  • no_of_adults: Number of adults
  • no_of_children: Number of Children
  • no_of_weekend_nights: Number of weekend nights (Saturday or Sunday) the guest stayed or booked to stay at the hotel
  • no_of_week_nights: Number of week nights (Monday to Friday) the guest stayed or booked to stay at the hotel
  • type_of_meal_plan: Type of meal plan booked by the customer:
  • required_car_parking_space: Does the customer require a car parking space? (0 - No, 1- Yes) room_type_reserved: Type of room reserved by the customer. The values are ciphered (encoded) by INN Hotels.
  • lead_time: Number of days between the date of booking and the arrival date
  • arrival_year: Year of arrival date
  • arrival_month: Month of arrival date
  • arrival_date: Date of the month
  • market_segment_type: Market segment designation.
  • repeated_guest: Is the customer a repeated guest? (0 - No, 1- Yes)
  • no_of_previous_cancellations: Number of previous bookings that were canceled by the customer prior to the current booking
  • no_of_previous_bookings_not_canceled: Number of previous bookings not canceled by the customer prior to the current booking avg_price_per_room: Average price per day of the reservation; prices of the rooms are dynamic. (in euros)
  • no_of_special_requests: Total number of special requests made by the customer (e.g. high floor, view from the room, etc)
  • booking_status: Flag indicating if the booking was canceled or not.

Source

https://www.kaggle.com/datasets/ahsan81/hotel-reservations-classification-dataset

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