Comments (1)
There is an example of the 'unique_id' and 'x' variables in the README.
https://github.com/kdgutier/esrnn_torch
The 'unique_id' identifies the univariate time series from your panel data. While the the 'x' categorical variable is a static variable (one hot encoded within the model) that shows a single discrete characteristic of the time series, that is constant over time.
from esrnn_torch.
Related Issues (20)
- Very short time series in unbalanced panel, assert n_windows>0 HOT 3
- How to set seasonality HOT 2
- application for time series data with trend HOT 1
- Saving Model HOT 1
- Why is numpy==1.16.1 the only numpy version compatible with ESRNN? HOT 1
- AssertionError: clean np.nan's from unique_idxs unbalanced Y_df HOT 10
- Save functionality broken; ESRNN Model Object structure not reflected in save & load
- Exogenous variables HOT 1
- Allow for more covariates / features HOT 1
- ES-RNN for long sequence time series forecasting? HOT 1
- Prediction interval for ES-RNN HOT 5
- Data Formatting for ES-RNN HOT 1
- Hourly results typo in the results table in readme? HOT 2
- input format of training and test data HOT 1
- Input for OWA Calculation - AttributeError HOT 2
- how to use continuous exogenous variable in the future for forecasting problem HOT 1
- Return NaN prediction
- How to prepare the data format? HOT 12
- problem with pandas HOT 1
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