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Stepwise-Interpretable-Machine-Learning

This open-source code for the short-term demand forecasting aims to demonstrate the way of integrating econometric models and deep learning methods, using New York taxi records (yellow taxi and for-hire vehicle (FHV)).

Published journal paper: Kim, T., Sharda, S., Zhou, X. and Pendyala, R.M., 2020. A stepwise interpretable machine learning framework using linear regression (LR) and long short-term memory (LSTM): City-wide demand-side prediction of yellow taxi and for-hire vehicle (FHV) service. Transportation Research Part C: Emerging Technologies, 120, p.102786. https://doi.org/10.1016/j.trc.2020.102786

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Stepwise framework using linear regression and advanced recurrent neural network (LSTM)

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