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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 profitable policies for cancelations & refunds.

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logistic-regression sklearn-library statsmodels scipy-stats variance-inflation-factor chi-squared-test roc-auc-curve precision-recall decision-tree-classifier confusion-matrix

classification-booking-cancelation-prediction-starhotels's Introduction

Hi, this is Rochita! ๐Ÿ‘‹

  • Based out of Vancouver, British Columbia ๐Ÿ”๏ธ
  • Interested in Data Science, Machine Learning & Big Data ๐ŸŒฑ
  • Currently learning more on Deep Learning (NLP & CV) ๐Ÿ“š
  • Check out some of my projects ๐Ÿ”ญ

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