easygraph.datasets.hypergraph.cocitation module#

class easygraph.datasets.hypergraph.cocitation.CocitationCiteseer(data_root: str | None = None)[source]#

Bases: BaseData

The Co-citation Citeseer dataset is a citation network dataset for vertex classification task. More details see the HyperGCN paper.

The content of the Co-citation Citaseer dataset includes the following:

  • num_classes: The number of classes: \(6\).

  • num_vertices: The number of vertices: \(3,312\).

  • num_edges: The number of edges: \(1,079\).

  • dim_features: The dimension of features: \(3,703\).

  • features: The vertex feature matrix. torch.Tensor with size \((3,312 \times 3,703)\).

  • edge_list: The edge list. List with length \(1,079\).

  • labels: The label list. torch.LongTensor with size \((3,312, )\).

  • train_mask: The train mask. torch.BoolTensor with size \((3,312, )\).

  • val_mask: The validation mask. torch.BoolTensor with size \((3,312, )\).

  • test_mask: The test mask. torch.BoolTensor with size \((3,312, )\).

Parameters:

data_root (str, optional) – The data_root has stored the data. If set to None, this function will auto-download from server and save into the default direction ~/.dhg/datasets/. Defaults to None.

class easygraph.datasets.hypergraph.cocitation.CocitationCora(data_root: str | None = None)[source]#

Bases: BaseData

The Co-citation Cora dataset is a citation network dataset for vertex classification task. More details see the HyperGCN paper.

The content of the Co-citation Cora dataset includes the following:

  • num_classes: The number of classes: \(7\).

  • num_vertices: The number of vertices: \(2,708\).

  • num_edges: The number of edges: \(1,579\).

  • dim_features: The dimension of features: \(1,433\).

  • features: The vertex feature matrix. torch.Tensor with size \((2,708 \times 1,433)\).

  • edge_list: The edge list. List with length \(1,579\).

  • labels: The label list. torch.LongTensor with size \((2,708, )\).

  • train_mask: The train mask. torch.BoolTensor with size \((2,708, )\).

  • val_mask: The validation mask. torch.BoolTensor with size \((2,708, )\).

  • test_mask: The test mask. torch.BoolTensor with size \((2,708, )\).

Parameters:

data_root (str, optional) – The data_root has stored the data. If set to None, this function will auto-download from server and save into the default direction ~/.dhg/datasets/. Defaults to None.

class easygraph.datasets.hypergraph.cocitation.CocitationPubmed(data_root: str | None = None)[source]#

Bases: BaseData

The Co-citation PubMed dataset is a citation network dataset for vertex classification task. More details see the HyperGCN paper.

The content of the Co-citation PubMed dataset includes the following:

  • num_classes: The number of classes: \(3\).

  • num_vertices: The number of vertices: \(19,717\).

  • num_edges: The number of edges: \(7,963\).

  • dim_features: The dimension of features: \(500\).

  • features: The vertex feature matrix. torch.Tensor with size \((19,717 \times 500)\).

  • edge_list: The edge list. List with length \(7,963\).

  • labels: The label list. torch.LongTensor with size \((19,717, )\).

  • train_mask: The train mask. torch.BoolTensor with size \((19,717, )\).

  • val_mask: The validation mask. torch.BoolTensor with size \((19,717, )\).

  • test_mask: The test mask. torch.BoolTensor with size \((19,717, )\).

Parameters:

data_root (str, optional) – The data_root has stored the data. If set to None, this function will auto-download from server and save into the default direction ~/.dhg/datasets/. Defaults to None.