Comments (2)
Hi Guillaume,
Not for the moment, the only datasets we provide are with a single channel per node. However, the library supports any custom-made dataset with multiple channels.
Cheers,
Ivan
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Hi Ivan,
Thanks, I used others variables in AQI to configure an imputation with multiples channels.
Cheers,
Guillaume
from tsl.
Related Issues (20)
- TypeError: on_train_batch_start() takes 3 positional arguments but 4 were given HOT 5
- The examples are not working, perhaps some info is missing HOT 5
- Differences of args in ImputationDataset between tsl-0.1.1 and the latest HOT 1
- The explanation of training mask and eval mask HOT 5
- Trouble with Hydra, perhaps other way to run the examples? HOT 1
- Method to specify save location of a dataset HOT 1
- error at test : test_example_imputation HOT 1
- Error while training the model in the example notebook: a_gentle_introduction_to_tsl.ipynb HOT 3
- Doubt about Masked Metric's init HOT 1
- Pandas version HOT 2
- Shapes of input data HOT 4
- Add parameter to specify which is the time dimension in MaskedMetric HOT 1
- [Improving Documentation] Contributing inspectable notebook for imputation on custom dataset HOT 2
- Update Lightning compatibility
- Please provide some suggestions for multi timeseries training
- sensor locations from pems08 HOT 2
- Is the definition of connectivity in the AirQuality dataset wrong? HOT 2
- SpatioTemporalDataset.from_dataset does not accept the transform parameter. HOT 1
- ScalerModule masks Scaler transform HOT 1
- Add future covariates HOT 2
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