update readme

README.md

@@ -18,6 +18,14 @@ The file `custom_dataset.py` contains the function `get_data_and_generate_train_
     - `normalize` (boolean): If set to `True`, data is normalized per-feature.
     - `transformer` (boolean): If set to `True` and `normalize` is also `True`, then categorical time features are not normalized. Useful for embedding said features in Transformers.
 
+The outputs are as follows:
+
+- `train`: `torch.utils.data.Dataset` containing the train data.
+- `val`: `torch.utils.data.Dataset` containing the validation data.
+- `test`: `torch.utils.data.Dataset` containing the test data.
+- `mean`: `np.ndarray` containing the featurewise mean. If `normalization` is `False`, then it defaults to all `0`s.
+- `std`: `np.ndarray` containing the featurewise standard deviation. If `normalization` is `False`, then it defaults to all `1`s.
+
 ## ComStock Notice
 
 This data includes information from the ComStock™ dataset developed by the National Renewable Energy Laboratory (NREL) with funding from the U.S. Department of Energy (DOE). This model was trained using ComStock release 2023.2. NREL regularly publishes updated datasets which generally improve the representation of building energy consumption. Users interested in training their own models should review the latest dataset releases to assess whether recent updates offer features relevant to their modeling objectives.