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A data analysis project on cab rides using Python and Machine Learning

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ML-Project

In order to look at the various factors that affect the pricing schemes of cab companies, we have performed data analysis on a relatively recent dataset (2018) containing simulated rides and their estimated prices, obtained by querying the API of the official Uber and Lyft online cab booking website over the months of November and December. We have used the following regression algorithms:

  • Linear Regression
  • Ridge Regression
  • Support Vector Regressor
  • Random Forest Regressor

Random forest gave us the best results with an R2 score of 0.96.

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A data analysis project on cab rides using Python and Machine Learning

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