Grape edge prediction # edges reported

[abbynewbury]

Hi!

I am using edge prediction evaluation and LogisticRegressionCVEdgePrediction for my graph, which has the following:

print(f"Number of edges in graph: {len(graph.get_edge_node_ids(directed=False))}") Number of edges in graph: 4541 print(f"Number of nodes in graph: {len(graph.get_node_ids())}") Number of nodes in graph: 1875.

However, when I run edge prediction evaluation: results = edge_prediction_evaluation( holdouts_kwargs=dict(train_size=0.8), graphs=graph, models=LogisticRegressionCVEdgePrediction(max_iter=500), number_of_holdouts=1, node_features=model ) where model = Node2VecSkipGramEnsmallen(embedding_size=EMBEDDING_SIZE,walk_length = WALK_LENGTH,return_weight = RETURN_WEIGHT, explore_weight=EXPLORE_WEIGHT, iterations=NUM_WALKS).fit_transform(graph)

I find that the results report: nodes_number: 1875 edges_number: 9082

I was wondering why the prediction is reporting double the number of edges than are actually present in the graph? Thanks!

[LucaCappelletti94]

You are most likely predicting an undirected graph, which is a graph where interactions go in both directions. So it is providing the prediction in both directions.