Valeriy
06/25/2022, 9:25 AMChris Gervais
07/01/2022, 11:55 AMNeuralProphet
ftwValeriy
08/17/2022, 9:35 PMChris Gervais
08/18/2022, 11:53 PMNeuralProphet
but always happy to try out other libraries 🙂 do you have a tutorial recommendation in statsforecast
for multi-step prediction with exogenous lagged + future regressors?statsforecast
and NeuralProphet
when more extensive hyperparam optimization is applied, this looks like a single architecture was used throughout: https://github.com/Nixtla/statsforecast/blob/main/experiments/neuralprophet/src/neuralprophet.py ... FWIW, we've found we need around ~70 NN architecture searches followed by about the same number of LR tuning runs, definitely not ideal but not unlike other NN approaches. fortunately the auto LR finder works reasonably well which makes the arch searches a lot more reasonable.
we'll try to bring in the example from https://github.com/Nixtla/statsforecast/blob/main/experiments/arima_xreg/src/statsforecast.py this weekend and report back on any interesting findings we come across!Valeriy
08/21/2022, 3:42 PMChris Gervais
08/29/2022, 3:40 PMNeuralProphet
consistently outperforms both AutoARIMA
and ETS
from statsforecast
on a wide range of power system forecasting tasks. i can't comment on whether this extends to other time series baseline datasets but i suspect the ERCOT baseline is very similar to our datasets. obviously the tuning time to get decent results is a disadvantage relative to AutoARIMA
and ETS
but it seems the same tradeoff exists between NeuralProphet
and Nbeats / N-HiTS
in that it's relatively quick to spin up decent models in NeuralProphet
whereas Nbeats / N-HiTS
requires a much more extensive hyperparmeter sweep to get comparable results.
we're still pretty new to the nixtla
ecosystem of open source forecasting tools though, so i'm sure there are many things we're doing wrong, happy to chat about opportunities for improving our integrations with either statsforecast
or neuralforecast
RandomForestRegressor
from sklearn
as our baseline in favour of AutoARIMA
from statsforecast
- works great and super efficient