MUTAGDatasetΒΆ
-
class
dgl.data.
MUTAGDataset
(print_every=10000, insert_reverse=True, raw_dir=None, force_reload=False, verbose=True, transform=None)[source]ΒΆ Bases:
dgl.data.rdf.RDFGraphDataset
MUTAG dataset for node classification task
Mutag dataset statistics:
Nodes: 27163
Edges: 148100 (including reverse edges)
Target Category: d
Number of Classes: 2
Label Split:
Train: 272
Test: 68
- Parameters
print_every (int) β Preprocessing log for every X tuples. Default: 10000.
insert_reverse (bool) β If true, add reverse edge and reverse relations to the final graph. Default: True.
raw_dir (str) β Raw file directory to download/contains the input data directory. Default: ~/.dgl/
force_reload (bool) β Whether to reload the dataset. Default: False
verbose (bool) β Whether to print out progress information. Default: True.
transform (callable, optional) β A transform that takes in a
DGLGraph
object and returns a transformed version. TheDGLGraph
object will be transformed before every access.
-
graph
ΒΆ Graph structure
- Type
Examples
>>> 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']