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HI! it is possibile to use your model for multivariate timeseries forecasting?
I want to predict one series with the help of other series
Thank you!.
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With the update to the `conda-forge` feedstock in #465 I've just upgraded from v3.0.0 to v3.2.1 of `sphinx-autoapi`, and am now getting errors like these when I run `sphinx-build`, which I never got b…
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**Describe the bug**
When clustering multivariate timeseries, KShapes returns the same cluster center for each dimension. When I generate 3-dimensional timeseries of 8 catogeries, TimeSeriesKMeans fi…
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Evolve (shapelet, k) with k the channel from which it must be extracted
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Scoringutils currently treats timeseries as independent when we score them. When you score forecasts for different locations, timeseries are correlated in a way that we don't take into account.
Ex…
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- PyTorch-Forecasting version: 0.9.1
- PyTorch version: 1.10.0
- Python version: 3.7.11
- Operating System: Linux Ubuntu
I am using the Pytorch Forecasting DeepAR Model for forecasting a multiv…
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**Is your feature request related to a problem? Please describe.**
Complexity of preprocessing/transforming data for LSTM networks.
**Describe the use case**
Most timeseries data come in the form…
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From what I see in the data of the repository and the repository of the [author](https://github.com/7fantasysz/MSCRED) the data have the following shape :
**(number of time series * lenght of time…
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From what I see in the data of this repository the data have the following shape :
**(number of time series * lenght of time series)**
However a multivatiate time serie should have the followi…
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I have been able to predict the result through single input, such as stock data, and forecast the following data through input of the closing price of the stock. Such prediction effect is not good, so…