Quick question: any suggestions for Intermittent demand forecasts ? Like products that are ordered only maybe bi weekly or whatever ? One week yes, one week no ?. We tried lightgbm, binary forecasting with lightgbm, prophet, IMAPA and ADIDA and our results are not great. only 60% accuracy in line with our moving average baseline.

Yes, intermittent demand is hard and sometimes and sometimes an average is better. You could also try croston. Thank two guides might be helpful.

@Valeriy could you eli5 me conformal prediction and it s advantages?

@Andrei Tulbure wrong thread for posting I was planning to post in general. Here is explanation for 2 year old https://www.tiktok.com/@rajistics/video/7145960334270975275

So it`s basically getting quantiles for the predictions?

@Andrei Tulbure no, conformal prediction is a general framework it does not produce quantiles as such what it produces are Prediction Intervals where true values are guarantees to lie in with user specified probability. Classical quantile regression does not produce true quantiles - just because it says 75% quantile there are no guarantees there will be 75 percent of observations below it. You can see an example of what it does and what is the difference here. NeuralProphet trained with quantile regression shown to provide miscalibrated intervals but Conformal Prediction has corrected it. So it can both produce prediction intervals that are well calibrated or alternatively correct prediction intervals from other models. https://valeman.medium.com/probabilistic-forecasting-with-conformal-prediction-and-neuralprophet-af9c87901d94