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andr830g / Machine-Learning-Passenger-Forecasting

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Bachelor thesis regarding bus passenger forecasting for line 1A-6A in Aarhus, Denmark. We evaluate classical naive and statistical models (Lasso) together with machine learning (Random Forest and XGBoost) and deep learning models (RNN and LSTM). We adopt Performance Based Shapley Values for "black-box" model explaination.

machine-learning deep-learning time-series shap passenger-forecasting midttrafik pbsv
  • Updated Jun 30, 2024
  • Jupyter Notebook

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