Comments (1)
Hi @Sirchko1,
We are currently centering our efforts in the NeuralForecast library. We are yet to include the ESRNN
but it is among our priorities.
We recommend to switch towards NeuralForecast, in the meantime. Among the available models we have: MLP
, RNN
, LSTM
, NBEATS
, NHITS
, and TFT
.
from esrnn_torch.
Related Issues (20)
- Example of use of the 'unique_id' and 'x' variables. HOT 1
- 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
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from esrnn_torch.