torch_geometric.datasets.CornellTemporalHyperGraphDataset
- class CornellTemporalHyperGraphDataset(root: str, name: str, split: str = 'train', setting: str = 'transductive', transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None, pre_filter: Optional[Callable] = None, force_reload: bool = False)[source]
Bases:
InMemoryDataset
A collection of temporal higher-order network datasets from the “Simplicial Closure and higher-order link prediction” paper. Each of the datasets is a timestamped sequence of simplices, where a simplex is a set of \(k\) nodes.
See the original datasets page for more details about individual datasets.
- Parameters:
root (str) – Root directory where the dataset should be saved.
name (str) – The name of the dataset.
split (str, optional) – If
"train"
, loads the training dataset. If"val"
, loads the validation dataset. If"test"
, loads the test dataset. (default:"train"
)setting (str, optional) – If
"transductive"
, loads the dataset for transductive training. If"inductive"
, loads the dataset for inductive training. (default:"transductive"
)transform (callable, optional) – A function/transform that takes in an
torch_geometric.data.Data
object and returns a transformed version. The data object will be transformed before every access. (default:None
)pre_transform (callable, optional) – A function/transform that takes in an
torch_geometric.data.Data
object and returns a transformed version. The data object will be transformed before being saved to disk. (default:None
)pre_filter (callable, optional) – A function that takes in an
torch_geometric.data.Data
object and returns a boolean value, indicating whether the data object should be included in the final dataset. (default:None
)force_reload (bool, optional) – Whether to re-process the dataset. (default:
False
)