License: MIT License
基于tensorflow2.4的图卷积网络，可用于图节点分类以及图分类
入口文件:train_gcn.py
示例样本:data文件夹中的文件，通过运行utils.py中的generate_sz函数生成，因为当图过大时，每次通过shp文件计算特征和邻接矩阵耗时过久，
所以需要提前将特征和邻接矩阵算好，然后直接通过读取
入口文件:train.py
暂未提供样本
data 图节点分类示例样本
utils.py 数据处理相关代码，包括特征提取，计算拉普斯拉矩阵等
model.py 模型架构，gcnnmodel是图分类模型，gcnmodel是图节点分类模型
metrics.py 用于图节点分类模型的评价指标，计算损失值和准确率
layers.py 卷积层和全连接层的相关代码
train.py 图节点分类模型的训练
train_gcn.py 图分类模型的训练
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