https://github.com/shahaba83/airplane-ticket-cancellation

In this project, we try to predict the possibility of canceling the plane ticket by the buyer
https://github.com/shahaba83/airplane-ticket-cancellation

datatime numpy pandas python scikit-learn seaborn

Last synced: 6 days ago
JSON representation

In this project, we try to predict the possibility of canceling the plane ticket by the buyer

• Host: GitHub
• URL: https://github.com/shahaba83/airplane-ticket-cancellation
• Owner: ShahabA83
• Created: 2024-09-15T14:01:50.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-09-15T15:04:37.000Z (about 2 months ago)
• Last Synced: 2024-10-31T13:04:22.814Z (6 days ago)
• Topics: datatime, numpy, pandas, python, scikit-learn, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 8.52 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# The subject of the project:

**In this project, we try to predict the possibility of canceling the plane ticket by the buyer**

---

### Pyhton:

This project is completely written in Python 



#### Required libraries:

  

 

---



Introduction to the dataset:





The data set contains 101017 rows, the description of each column is given in the table below





    

|Column|Description|

|:------:|:---:|

|Created|Ticket registration time|

|CancelTime|When the passenger canceled the ticket|

|DepartureTime|Time to move|

|BillID|Purchase ID|

|TicketID|Ticket ID|

|ReserveStatus|Customer payment status|

|UserID|UserID|

|Male|Does the ticket belong to a woman or a man|

|Price|Ticket price without discount|

|CouponDiscount|Discount applied by the person on the ticket|

|From|Origin of travel|

|To|Travel destination|

|Domestic|Is the trip domestic or foreign|

|VehicleType|Specifies the details of the car|

|VehicleClass|Is it a first class vehicle or not|

|Vehicle|Vehicle type|

|HashPassportNumber_p|HashPassport|

|HashEmail|HashEmail|

|BuyerMobile|BuyerMobile|

|NationalCode|NationalCode|

|TripReason|Reason for travel|

|Cancel|Is the ticket canceled or not|

---

### Accuracy Model:

In this project, the accuracy of the model reaches 99%