Question

我正在使用adamic_adar索引进行链接预测问题。数据集是一个网格网络（具有1000个链接的边列表）。我从观察到的数据集中随机选择了80％（800）的边缘。我需要从如下所示的preds中选择最高的200条预测链接，并计算出准确率。我不知道下一步该怎么做。我该怎么办..帮助！

import numpy as np
import networkx as nx


G = nx.read_edgelist('Grid.txt', create_using=nx.Graph(), nodetype=int)
preds = nx.adamic_adar_index(G);
for u, v, p in preds:
    '(%d, %d) -> %.8f' % (u, v, p)
    print(u, v, p)

Answer 1

我假设u，v是图形的顶点，p是精度。

import numpy as np
import networkx as nx
import random

G = nx.read_edgelist('Grid.txt', create_using=nx.Graph(), nodetype=int)
preds = nx.adamic_adar_index(G)
preds = random.sample(preds, int(len(preds)*0.8))
preds = sorted(preds, key=lambda x: x[2], reverse=True)[:200]
ratio = sum([t[2] for t in preds])/len(preds)
print(ratio)

Answer 2

import numpy as np
import networkx as nx
import random

G = nx.read_edgelist('Grid.txt', create_using=nx.Graph(), nodetype=int)
preds = list(nx.adamic_adar_index(G))
preds = random.sample(preds, int(len(preds)*0.8))
preds = sorted(preds, key=lambda x: x[2], reverse=True)[:200]
ratio = sum([t[2] for t in preds])/len(preds)
print(ratio)

如何在python中编写用于链接预测精度评估的代码？

2 个答案: