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AnacletoLAB / grape

🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations

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Grape edge prediction # edges reported

abbynewbury opened this issue · comments

commented

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!

commented

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.