30lm32 / ml-imbalanced-car-booking-data

Create a ML model using Random Forest Classifier over skew (imbalanced) booking data

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Why do customers choose and book specific vehicles?

Problem Data Methods Libs Link
Imbalanced Data Car Booking Random Forest Classifier Sklearn, Pandas, Seaborn https://github.com/erdiolmezogullari/ml-imbalanced-car-booking-data

If you want to see the further ML projects, you may visit my main repo: https://github.com/erdiolmezogullari/ml-projects

We built a machine learning model that answers the question, -what is the customer preference- on car booking dataset.

We explored the dataset by using Seaborn, and transformed, derived new features necessary.

In addition, the shape of dataset is imbalanced. It means that the target variable's distribution is skewed. To overcome that challenge, there are already defined a few different techniques (e.g. over/under resampling techniques) and intuitive approaches. We try to solve that problem using resampling techniques, as well.

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Create a ML model using Random Forest Classifier over skew (imbalanced) booking data


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