I asked a similiar question in the #general channel regarding ensembles about a week ago. Haven't received any responses. Hope it is ok to repost a similar question in this channel. The sklearn

votingregressor

works within #mlforecast--in the sense it produces a result not a warning or failed run. Here are my questions: • Is #mlforecast supposed to be able to use the

votingregressor

? • Even though I'm not specifying any weights, the

votingregressor

does not produce true averages. Is there something I'm missing? • How are the prediction intervals derived? I'm coming from the

R

fable

world where you have to generate sample paths to derive prediction intervals for ensembles. Just wondering if what it is producing for PIs is accurate. • The previous

nixtla

package had a built-in ensemble forecaster. I have not been able to find such a function/method in the current

statsforecast

or

mlforecast

pacakges. If it exists can someone point me to documentation? • If there is an ensembl forecaster, can you use it across SF and MLF? Thanks! #ensemble #combinationmodel