This project focuses on predictive modeling for traffic accident severity in the US using machine learning. Leveraging the Kaggle US Accidents dataset, the objective is to analyze accident trends and contributing factors. The project will deploy and assess Random Forest, MLP Classifier, and LightGBM models to predict accident severity.
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This project focuses on predictive modeling for traffic accident severity in the US using machine learning. Leveraging the Kaggle US Accidents dataset, the objective is to analyze accident trends and contributing factors. The project will deploy and assess Random Forest, MLP Classifier, and LightGBM models to predict accident severity.
megh-3112/Predictive-Modelling-for-Traffic-Accident-severity-in-the-US-using-Machine-Learning-
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This project focuses on predictive modeling for traffic accident severity in the US using machine learning. Leveraging the Kaggle US Accidents dataset, the objective is to analyze accident trends and contributing factors. The project will deploy and assess Random Forest, MLP Classifier, and LightGBM models to predict accident severity.
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