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**Describe the bug**
With Sktime 0.25.0 the WindowSummarizer returns unexpected missing values.
**To Reproduce**
```python
import numpy as np
import pandas as pd
from sktime.transformati…
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### Describe the feature or idea you want to propose
currently test_all_forecasters takes 45 minutes on my machine (down from over an hour after https://github.com/aeon-toolkit/aeon/pull/568). I th…
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### Describe the feature or idea you want to propose
Update 6/2/24
forecasting
testing
transformers
utils
in the continued efforts to isolate the horrible datatypes…
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Now consider if we are executing the proof of this statement right now or not and we have constructed a neat logical box that can be true or false in a very self referential manner!
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A common forecasting or transformation workflow is like this:
* first conduct a seasonality test, then deseasonalize; then possibly forecast
* first conduct a stationarity test, then difference; t…
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**Submitting author:** @lexcomber (Alexis Comber)
**Repository:** https://github.com/lexcomber/stgam
**Branch with paper.md** (empty if default branch): description
**Version:** 0.0.1.1
**Editor:** Pe…
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Above are histograms of posterior probability distri…
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- [x] prepare `XGBoostForecaster` class
- [x] compare with `CatBoostForecaster` class
- [ ] use Hierarchical forecasting on both + `ProphetForecaster`
-> Features to use as hierarchy
…
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1D Convolutional Neural Networks (1D CNNs) can be highly effective for time series forecasting due to their ability to detect local temporal patterns and their capacity to handle sequential data.
1…
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Hi, great works! I have questions about datasets mentioned in your paper and models which you use to compare with PDFormer.
I noticed the max number of nodes of datasets is 1024(T-Drive), which is…