MUTAG数据集

class dgl.data.MUTAGDataset(print_every=10000, insert_reverse=True, raw_dir=None, force_reload=False, verbose=True, transform=None)[source]

Bases: RDFGraphDataset

用于节点分类任务的MUTAG数据集

Mutag 数据集统计：

节点数：27163
边数：148100（包括反向边）
目标类别: d
班级数量：2
标签分割：
- 训练：272
- 测试: 68

Parameters:

print_every (int) – Preprocessing log for every X tuples. Default: 10000.
insert_reverse (bool) – If true, add reverse edge and reverse relations to the final graph. Default: True.
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.
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.

num_classes

预测的类别数量

Type:: int

predict_category

具有预测标签的实体类别（节点类型）

Type:: str

graph

图结构

Type:: dgl.DGLGraph

示例

>>> dataset = dgl.data.rdf.MUTAGDataset()
>>> graph = dataset[0]
>>> category = dataset.predict_category
>>> num_classes = dataset.num_classes
>>>
>>> train_mask = g.nodes[category].data['train_mask']
>>> test_mask = g.nodes[category].data['test_mask']
>>> label = g.nodes[category].data['label']

__getitem__(idx)[source]

获取图形对象

Parameters:

idx (int) – 项目索引，MUTAGDataset只有一个图对象

Returns:

The graph contains:

ndata['train_mask']: mask for training node set
ndata['test_mask']: mask for testing node set
ndata['label']: node labels

Return type:

dgl.DGLGraph

__len__()[source]

数据集中图的数量。

Return type:: int