Models and Predictions for "The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow Prediction"

<strong>Models and Predictions</strong> This dataset contains the trained XGBoost and EA-LSTM models and the models' predictions for the paper <em>The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow Prediction</em>. For each combination of model (XGBoost, EA-LSTM), training years (3, 6, 9), number of basins (13, 26, 53, 265, 531), and seed (111-888), there are five folders. Each corresponds to a random basin sample (for 531 basins there's only one folder, since it's all basins).<br> In each folder, there are two files: \(\texttt{model.pkl}\) (XGBoost) or <em>\(\texttt{model_epoch30.pt}\)</em> (EA-LSTM), which stores the pickled trained model <em>\(\texttt{xgboost_seedNNN.p}\)</em> or <em>\(\texttt{ealstm_seedNNN.p}\)</em>, which stores a pickled dictionary that maps each basin to the DataFrame of predicted and actual daily streamflow. In addition to each folder, there is a SLURM submission script called <em>\(\texttt{&lt;foldername&gt;.sbatch}\)</em> that was used to create and evaluate the model in the folder.