Repository for hotel Cancellations project for Suffolk construction
Objective: This project aims to develop a predictive model to address the rising cancellation rates for a hotel chain. The model predicts the likelihood of a reservation being canceled using the "Hotel Booking Demand" dataset, which includes reservation details for City and Resort hotels. The model is trained on data from 2015-2016 and tested on 2017 data. Scope: The analysis focuses on identifying key predictors of reservation cancellations and deploying the model in the hotel chain's booking system.
Table of Contents:
- hotel_bookings.csv is the imported data to the ipynb
- likehood_cancellations_hotelReservations.ipynb is the main notebook with EDA, model prep and model build of the final model
Installations: download the csv to your local working folder Packages required to run this notebook are listed in the import packages part of the notebook. Make sure to pip install these packages to successfully run the notebook Make sure to change the location of the csv read in path to your current folder where the csv is stored in the import data part of the notebook
This current version is a readme only and is not to be edited