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https://github.com/raksh710/healthcare_analytics

The task is to correctly predict the number of days a patient would be staying in a hospital, out of 10 different categories. 16 different parameters were given. EDA, Feature Engineering, resampling has been performed to properly do data preprocessing. Ultimately CatBoost Classification model has been implemented to achieve more than 41% accuracy.
https://github.com/raksh710/healthcare_analytics

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The task is to correctly predict the number of days a patient would be staying in a hospital, out of 10 different categories. 16 different parameters were given. EDA, Feature Engineering, resampling has been performed to properly do data preprocessing. Ultimately CatBoost Classification model has been implemented to achieve more than 41% accuracy.

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