Our ETS is 30% faster and 100 times faster than Ne...
# generalm
Max (Nixtla)
08/17/2022, 2:48 PMOur ETS is 30% faster and 100 times faster than NeuralProphet: https://www.linkedin.com/posts/mergenthaler_timeseries-forecasting-statistics-activit[…]yNtW?utm_source=linkedin_share&utm_medium=member_desktop_web
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Max (Nixtla)
08/17/2022, 2:49 PM@Valeriy: its settled, NeuralProphet is also sort of broken.
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Kin Gtz. Olivares
08/17/2022, 2:58 PMGuys at Facebook should stop burning millions in the Metaverse and build reasonable forecasting algorithms.
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Valeriy
08/17/2022, 2:59 PMHaha you guys have smoked🔥 Neural Prophet. Great work from Nixtla again
Valeriy
08/17/2022, 5:00 PMAs everyone knows I am a huge sceptic of Prophet, I have done some initial limited explorations of Neural Prophet beginning of this year but then didn't have time as started new role.
https://valeman.medium.com/benchmarking-facebook-prophet-53273c3ee9c6
https://valeman.medium.com/benchmarking-neural-prophet-part-i-neural-prophet-vs-prophet-252990763468
https://valeman.medium.com/benchmarking-neural-prophet-part-ii-exploring-electricity-dataset-4cade7b2431c
TL;DR Results were somewhat better than Prophet as including autoregressive terms helped, but not conclusive.
Great comprehensive work evaluating it across multiple datasets.
Valeriy
08/17/2022, 5:03 PM@Max (Nixtla) it is settled bigly, I didn't pin big hopes on it as it is still curve fitter but AR terms were improvement even then my own tests indicated “deepAR” didn't improve much compared to linear AR. Even then to see it losing to ES is big news.
Valeriy
08/17/2022, 5:14 PMMy Twitter thread on it, https://threadreaderapp.com/thread/1559948624548741123.html
Valeriy
08/21/2022, 11:53 AM@Max (Nixtla) @Kin Gtz. Olivares quick question - what sort of ES model is under the hood? Is there some document describing it, presumably it is some sort of similar to auto ARIMA with automatic hyperparameter optimisation?
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Max (Nixtla)
08/21/2022, 3:27 PMHi @Valeriy, we have been working on the documentation of the library. In the model section of the library, you can find some further info https://nixtla.github.io/statsforecast/models.html#exponential-smoothing-methods
Basically, we ported the ETS from Rob. (https://otexts.com/fpp3/expsmooth.html) here is more info on the optimization algorithm itself: https://otexts.com/fpp3/expsmooth.html
If you miss anything in the docs, please tag @MarianaR so we can include it and make the docs more straightforward.
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Max (Nixtla)
08/21/2022, 3:35 PMI was editing the post and I erased the other thing I wrote about the nelder mead. Either way, we are preparing a post explaining that particular aspect and making that particular optimization method available to the community.
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Valeriy
08/21/2022, 3:41 PMNice, thanks for sharing. Got to see SKTime opened their lib to other implementations.
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Kin Gtz. Olivares
08/21/2022, 3:42 PMThey had to
Theirs/StatsModels is broken
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