-
From my own experience, there are (at least) two very different use cases to use dataframes:
1. Doing some real-time data analysis in notebooks
2. Building production pipelines
While I think pand…
-
# Notebook Review: Issue #236
**Submitting author:** @bnubald
**Repository:** https://github.com/eds-book-gallery/67a1e320-7c47-4ea9-8df8-e868326bc90b
**Notebook…
-
Hello, I just want to make sure I am understanding correctly about how prediction intervals are used. I've been reading the documentation and code, but it's a bit difficult to comprehend without pulli…
-
Implementation of a pipeline for producing seasonal Arctic Sea ice forecasts using IceNet
---
**Supervisor:** @annefou @j34ni
**For degree:** Master
**Status:** Open
**Keywords:** climate - de…
-
**Is your feature request related to a current problem? Please describe.**
Is there any documentation related to implementing custom models in darts? I didn’t find it.
I browsed some related issues.…
-
It would be great to integrate this package - and adjacent ones like `LightGBMLSS` - with `skpro`, which in turn directly integrates with `sktime` for time series forecasting.
(both of course integat…
-
For a while I have now been thinking about what a good plotting modality would be for fully distributional predictions, i.e., the output of `predict_proba` in `sktime` or `skpro`.
The challnge is t…
-
When we forecast futures values, there is always uncertainty around the values that needed to be quantified. This is called risk. It would be nice if we can provide a probabilistic forecast around the…
-
We know that LightGBM currently supports quantile regression, which is great, However, quantile regression can be an inefficient way to gauge prediction uncertainty because a new model needs to be bu…
-
It would be great if one or more surface variables related to solar energy for solar power forecasting, like downward short-wave radiation flux/surface solar radiation downwards or total cloud cover, …