#neural-forecast

Title

t

Tyler Nisonoff

05/16/2023, 9:40 PMHaving trouble thinking through how to fit a current forecasting problem into the neuralforecast model:
Suppose every day at 10am, I want to predict tomorrows 24 hours worth of prices for some series (midnight to midnight).
It seems that currently the assumption is if I'm predicting time t -> t+horizon, I have data up to t-1. But in this case, I only have data up to

`t-14`

as i do not yet have prices from 11am-midnight
I could extend the horizon to be `24+14`

to predict 10am -> 12am the next day, but then in training / fit we'd step by the horizon, instead of just stepping forward 10 days.
is there some way to fit this into the neuralforecast approach?I found https://github.com/Nixtla/neuralforecast/discussions/470
which suggests filtering out prediction values for the first p results, but would this model step

`p+h`

hours when fitting the model?c

Cristian (Nixtla)

05/17/2023, 12:24 AMHi **@Tyler Nisonoff**. This seems to be a particular case that it can't be currently handled. There are partial solutions, like increasing the forecast horizon and changing

`step_size`

to be 24h instead of the horizon.👍 1