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Accident level prediction based on categorical features

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Kaggle accident level prediction problem

Accident level prediction based on categorical features

Most of the data is categorical so I tried to use decision tress and random forests. Tried to do some feature engineering. Tried different variations in feature engineering like : one hot encoding, removing features based on variance...

I have 10 -15 variantions of these files with different hyperparameters tuning.

Final accuracy i could get is around 92%

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