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Related to #194, I could not find out how the model output is validated against out-of-sample data in the model overview or any of the cited papers (apologies if missed). Do we need some code to per…
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We want to write a short gdoc explaining how a financial time series problem can be formulated in the classical ML paradigm of supervised learning.
Many prediction problems (e.g., price, volatility, …
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I notice this merge from the past: https://github.com/ourownstory/neural_prophet/pull/691/files
Just to make sure I understand here: I'm not seeing these methods in the forecaster.py any longer. Is…
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We will update the time series tables in the following days, aiming to provide a cleaner and more organized dataset consistent with our new/current naming convention. We will also be reporting a new v…
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Complete the following module checks on the AWS academy portal.
- [x] Module 4 - Time series forecasting.
- [x] Module 5 - Computer vision.
- [x] Module 6 - NLP
- [x] Module 7 - Generative AI
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**Is your feature request related to a problem? Please describe.**
- sktime stores trained y and trained X in the internal memory of the forecast as `self._y` and `self._X`. To my knowledge, this is …
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Hello,
I am currently working on a project involving univariate time series prediction and I am interested in using TimesNet for my dataset. My dataset is structured similarly to the ETTh1 dataset …
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## Expected Behavior
Passed integration test:
https://github.com/aimclub/FEDOT/blob/0bdece11af60d6e9abc84a894ddd66ea960b5611/test/integration/real_applications/test_examples.py#L86-L88
## Current…
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**Describe the bug**
Getting the below error on a remote server with the same notebook on the same data (runs fine on my local machine). Version of sktime is also the same.
```
TypeError: X must …