2dataset = dgl.data.CoraGraphDataset() 3print('Number of categories:', dataset.num_classes) 4g = dataset[0] 上面第二行代码,加载dgl库提供的Cora数据对象,第四行代码,dgl库中Dataset数据集可能是包含多个图的,所以加载的dataset对象是一个list,list中的每个元素对应该数据的一个graph,但Cora数据集是由单...
{dataset.num_classes}')data=dataset[0]# Get the first graph object. 这个数据集中只有一张图print()print(data)print('===')# Gather some statistics about the graph.print(f'Number of nodes: {data.num_nodes}')print(f'Number of edges: {data.num_edges}')print(f'Average node degree: ...
# `train_loader` computes the k-hop neighborhood of a batch of nodes, # and returns, for each layer, a bipartite graph object, holding the # bipartite edges `edge_index`, the index `e_id` of the original edges, # and the size/shape `size` of the bipartite graph. # Target nodes ...
需要配置win7的hosts文件： 打开地址：C:\Windows\System32\drivers\etc\hosts 用记事本打开，然后...
deep-learningpytorchgraph-convolutional-networksgcncora UpdatedDec 17, 2021 Python Redamancy-CX330/GCN_for_Node_Classification_Task Star4 An implementation of the Graph Convolution Networks for the Cora, Citeseer, PubMed dataset. deep-learningpytorchpubmedgraph-convolutional-networksgcncorapygciteseer ...
dataset = Planetoid("/tmp/Cora", name="Cora") num_nodes = dataset.data.num_nodes # For num. edges see: # - https://github.com/pyg-team/pytorch_geometric/issues/343 # - https://github.com/pyg-team/pytorch_geometric/issues/852 ...
图神经网络(Graph Neural Network,GNN)是使用神经网络来学习图结构数据,提取和发掘图结构数据中的特征和模式,满足聚类、分类、预测、分割、生成等图学习任务需求的算法,如图节点分类,图关系预测,社区发现,网络相似度。图卷积网络(Graph Convolutional Network,GCN),图注意力网络(Graph Attention Network,GAT),cora数据集...
在DGL的较新版本中,用于加载Cora数据集的正确类应该是CoraGraphDataset,而不是CoraDataset。这个类位于dgl.data模块下,而不是dgl.data.citation_graph。 提供替代方案或修正代码的建议: 您应该修改您的代码,使用正确的类名来加载Cora数据集。以下是一个示例代码片段,展示了如何正确使用CoraGraphDataset: python import...
Each publication in the dataset is described by a 0/1-valued word vector indicating the absence/presence of the corresponding word from the dictionary. 翻译过来就是: === Cora数据集,该数据集由 2708 篇论文,及它们之间的引用关系构成的 5429 条边组成。这些论文被根据主题划分为7类,分别是神经网络...
The Cora dataset consists of 2708 scientific publications classified into one of seven classes. The citation network consists of 5429 links. Each publication in the dataset is described by a 0/1-valued word vector indicating the absence/presence of the c