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* Add ChickenPox export
* Add ChickenPox dataset export
* Add ChickenPox test
* Add ChickenPox dataset
* Fix a alphabetical order
* Add more info and example
* Add more tests
The ChickenPox dataset contains county-level chickenpox cases in Hungary between 2004 and 2014.
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`ChickenPox` is composed of a graph with nodes representing counties and edges representing the neighborhoods, and a metadata dictionary containing the correspondence between the node indices and the county names.
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The node features are the number of weekly chickenpox cases in each county. They are represented as an array of arrays of size `(1, num_nodes, num_timesteps_in)`. The target values are the number of weekly chickenpox cases in each county. They are represented as an array of arrays of size `(1, num_nodes, num_timesteps_out)`. In both cases. two consecutive arrays are shifted by one-time step.
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The dataset was taken from the [Pytorch Geometric Temporal repository](https://pytorch-geometric-temporal.readthedocs.io/en/latest/modules/dataset.html#torch_geometric_temporal.dataset.chickenpox.ChickenpoxDatasetLoader) and more information about the dataset can be found in the paper ["Chickenpox Cases in Hungary: a Benchmark Dataset for
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Spatiotemporal Signal Processing with Graph Neural Networks"](https://arxiv.org/pdf/2102.08100).
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# Keyword Arguments
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- `normalize::Bool`: Whether to normalize the data using Z-score normalization. Default is `true`.
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- `num_timesteps_in::Int`: The number of time steps, in this case, the number of weeks, for the input features. Default is `8`.
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- `num_timesteps_out::Int`: The number of time steps, in this case, the number of weeks, for the target values. Default is `8`.
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- `dir::String`: The directory to save the dataset. Default is `nothing`.
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