evaluation code

[binxuan]

Hi,

Do you mind releasing the code you used for evaluation?

I am trying the multilabel classification on the BlogCatalog data. However, I can only get macro-f1 about 0.15 with 50% training data. My parameter setting is as follows: length of walk: 80, walks per node: 10 context window size: 10 dimension: 128 epoch: 1 p,q : 1 1 vs Rest Logistic regression with 0.01 L2 regularization.

[xgfs]

Probably too late to answer, but I was able to reproduce the results with DeepWalk's evaluation code: https://github.com/phanein/deepwalk/blob/master/example_graphs/scoring.py

Note that you are also feeding the correct number of classes to the classifier, therefore the evaluation is not perfectly fair (against a dataset).

[Juicechen95]

I also use the Deeowalk's evaluation code. However, I can only get macro-f1 about 0.21 with 50% training data. My parameter setting is as follows: length of walk: 80, walks per node: 10 context window size: 10 dimension: 128 epoch: 1 p,q : 1

change the p,q to 0.25, the macro-f1 is 0.23 .

I trained embeddings by node2vec with blogcatalog.edgelist file. And then use Deepwalk's evaluation which uses blogcatalog.mat file.

how can I reproduce the results?