Traffic flow prediction using ensemble methods.

Run command below to train the model:

python train.py --model model_name --data data_name

You can choose "rf","lstm","gru","saes","en_1","en_2", or "en_3" as arguments for model. You can choose "pems" pr "nyc" as arguments for data. The .h5 weight file was saved at model folder. "model_pems" folder contains the trained model for pems data and "model_nyc" contains the trained model of Bike NYC data.

Run command below to run the program:

python main.py --data data_name

You can choose "pems" or "nyc" as arguments for data.