PubmedGraphDataset

class dgl.data.PubmedGraphDataset(raw_dir=None, force_reload=False, verbose=True, reverse_edge=True, transform=None, reorder=False)[source]

Bases: CitationGraphDataset

Pubmed引文网络数据集。

节点代表科学出版物，边代表引用关系。每个节点都有一个预定义的500维特征。该数据集是为节点分类任务设计的。任务是预测某些出版物的类别。

统计：

节点数：19717
边数: 88651
班级数量：3
标签分割：
- 训练集: 60
- 有效: 500
- 测试: 1000

Parameters:

raw_dir (str) – Raw file directory to download/contains the input data directory. Default: ~/.dgl/
force_reload (bool) – Whether to reload the dataset. Default: False
verbose (bool) – Whether to print out progress information. Default: True.
reverse_edge (bool) – Whether to add reverse edges in graph. Default: True.
transform (callable, optional) – A transform that takes in a DGLGraph object and returns a transformed version. The DGLGraph object will be transformed before every access.
reorder (bool) – Whether to reorder the graph using reorder_graph(). Default: False.

num_classes

标签类别数量

Type:: int

注释

节点特征是行归一化的。

示例

>>> dataset = PubmedGraphDataset()
>>> g = dataset[0]
>>> num_class = dataset.num_of_class
>>>
>>> # get node feature
>>> feat = g.ndata['feat']
>>>
>>> # get data split
>>> train_mask = g.ndata['train_mask']
>>> val_mask = g.ndata['val_mask']
>>> test_mask = g.ndata['test_mask']
>>>
>>> # get labels
>>> label = g.ndata['label']

__getitem__(idx)[source]

获取图形对象

Parameters:

idx (int) – 项目索引，PubmedGraphDataset 只有一个图对象

Returns:

graph structure, node features and labels.

ndata['train_mask']: mask for training node set
ndata['val_mask']: mask for validation node set
ndata['test_mask']: mask for test node set
ndata['feat']: node feature
ndata['label']: ground truth labels

Return type:

dgl.DGLGraph

__len__()[source]: 数据集中图的数量。