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Hi,Palash Goyal When I try to run link prediction by adding the following code in my example
models.append(HOPE(d=4, beta=0.01))
for embedding in models: print ('Num nodes: %d, num edges: %d' % (G.number_of_nodes(), G.number_of_edges())) t1 = time() # Learn embedding - accepts a networkx graph or file with edge list Y, t = embedding.learn_embedding(graph=G, edge_f=None, is_weighted=True, no_python=True) print (embedding._method_name+':\n\tTraining time: %f' % (time() - t1)) # MAP, prec_curv, err, err_baseline = gr.evaluateStaticGraphReconstruction(G, embedding, Y, None) MAP,prec_curv = lp.evaluateStaticLinkPrediction(G,embedding,0.8,is_undirected = False)
I got the error:
nx.weakly_connected_component_subgraphs(train_digraph), AttributeError: module 'networkx' has no attribute 'weakly_connected_component_subgraphs'.
This may be the version of networkx. when I tried to use Networkx = 1.11, there will be other errors
How can I solve it?
The text was updated successfully, but these errors were encountered:
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Hi,Palash Goyal
When I try to run link prediction by adding the following code in my example
models.append(HOPE(d=4, beta=0.01))
I got the error:
This may be the version of networkx. when I tried to use Networkx = 1.11, there will be other errors
How can I solve it?
The text was updated successfully, but these errors were encountered: