Hello Nixtla team.

I am making a Machine Learning model, but it turns out that I have the following problem when I make the predictions with the predict method by adding the level(confidence interval) parameter, it gives me an error, 
                                                                                           mlf.fit(df1, id_col='unique_id', time_col='ds', target_col='y',prediction_intervals=PredictionIntervals(n_windows=5, window_size=18))

Are you trying to do something like this?

from statsforecast.core import StatsForecast
from statsforecast.models import ( 
    AutoARIMA,
    AutoETS,
)
from statsforecast.utils import generate_series, ConformalIntervals

series = generate_series(5)

sf = StatsForecast(
    models=[AutoETS(season_length=7)],
    freq='D',
)
# sf.forecast(df=series, h=horizon).head()
sf.fit(series, prediction_intervals=ConformalIntervals(n_windows=2, h=10))
sf.predict(18, level=[20,30])

Hi @Kevin Kho Something like this but with Mlforecast, with statsforecast there is no problem

Ah gotcha, I am less familiar with MLForecast

@José Morales: could you try to help Naren?

I've answered the issue, I think it's more beneficial to have this conversation there

Thanks! I wasn’t aware of that.

https://nixtlacommunity.slack.com/archives/C031M8RLC66/p1688397461750749 @José Morales i think i have error in same reshape function could you give me your opinion?

I think this can happen if there's a gap in your series, e.g. a missing day

i thought that also but i am not sure so can i choose the window size to be not this happend do you have idea?

Do you have a single serie?

yes i have single @José Morales

No, I just think it may be easier to debug. Can you try the following: df['ds'].sort_values().diff().value_counts() to see if there's a gap?

0 days 010000 4703 73 days 210000 1 1 days 040000 1 0 days 020000 1 0 days 060000 1 2 days 150000 1 here the output

Your series need to have a regular frequency, seems like you have mostly 1 hr differences but some observations are very far apart. If you don't care about the dates you can just use an incremental integer as the time column

what do you mean what do you mean by regular frequency i have data every 1 hour but in january for example doesnt have data

Yes, you need to fill the gap so that the diff command above returns a single value

you mean return 0 instead of 73 for example?

Yes, all of your samples should be one hour apart. If you don't have data for that period you need to fill it with 0s, interpolate or similar

but if i dont have data for one month this a big priode right ?

That would work as well