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cost-complexity-pruning

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The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate prof…

  • Updated Jan 20, 2022
  • Jupyter Notebook

A hotel chain is having issues with cancellations. This project analyzes customer booking data to identify which factors significantly influence cancellations, build models using logistic regression and decision trees to predict cancellations in advance, and help formulate profitable policies for cancellations and refunds for the hotel group

  • Updated Mar 20, 2023
  • Jupyter Notebook

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