-
In the evaluation method data from the second year is transformed by the model.
Previewing the predictions I see 7 values for ForecastedRentals in the results. I assumed that is because of the horizo…
-
Dear Authors,
Thank you for your invaluable contributions to this repository. I am currently exploring the field of time series imputation and have encountered some aspects regarding the evaluation…
-
## Description
I was running Evaluator and got an error below:
```
2 from gluonts.evaluation import Evaluator
3 evaluator = Evaluator(quantiles=[0.1, 0.5, 0.9], num_workers=None)
--…
-
Use case would be for evaluation purposes, to identify whether a given forecast contains all desired quantiles, locations, targets. Skeleton might look like this:
input: a single forecast in standa…
-
we should have an open discussion about what quantities of the forecast should appear as meta data in an evaluation result file. this comes from the fact that im working with !~1750 forecasts all havi…
-
Thanks for open sourcing your work! I just had a comment on the model performance evaluation.
It looks like this package checks the best out-of-sample forecast for the last set of values of `test_s…
-
## Description
```calculate_seasonal_error``` is buggy when the inputs are multivariate data.
```past_data = extract_past_data(time_series, forecast)``` results in ```(dim, time)``` shaped array rat…
-
Hi,
I'm using deepar for my dataset. But the results I got are rather frustrating. I'm confused why the width of the prediction intervals are so narrow, and it can not cover the observed values well.…
-
# Challenge 22 - XAI for Weather Forecasting Models (Transformer Embeddings)
> **Stream 2 - Machine Learning for Earth Sciences applications**
### Goal
Welcome to the XAI Transformer Embedding …
-
**Is your feature request related to a problem? Please describe.**
In the Feb 2 meeting it was discussed that some behaviours in evaluation might actually be "business of the model" rather than of th…