https://analyticsindiamag.com/facebook-prophets-existential-crisis/ prophet in the news again

NeuralProphet

ftw

Sure @Chris Gervais https://www.reddit.com/r/MachineLearning/comments/wqrw8x/d_fool_me_once_shame_on_you_fool_me_twice_shame/

Definitely interesting! We've had a lot of success with

NeuralProphet

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?

@Chris Gervais please share will be interesting to see the results

okay, we still need to do some more testing but so far we're finding that a properly tuned model from

NeuralProphet

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