数据集切分

[justforyou2017]

dataset = Planetoid(root='~/dataset/Cora', name='Cora')

Cora()

print(len(dataset))

1

print(dataset.num_classes)

7

print(dataset.num_node_features)

1433

data = dataset[0]

Data(edge_index=[2, 10556], test_mask=[2708],

train_mask=[2708], val_mask=[2708], x=[2708, 1433], y=[2708])

print(data.is_undirected())

True

print(data.train_mask.sum().item())

140

print(data.val_mask.sum().item())

500

print(data.test_mask.sum().item())

1000

+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

如上
1、请问训练集的数据量为何远远小于验证集和测试集呢？
2、如上数据集是2708个点，三个数据集为何不充分利用样本点数呢，即140+500+1000为何不等于2708
谢谢