From c7dedd570033f1c48dbd2379a652749d6b1d07ff Mon Sep 17 00:00:00 2001 From: William L Hamilton Date: Wed, 31 May 2017 08:41:44 +0100 Subject: [PATCH] Update README.md --- README.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/README.md b/README.md index e02a8d7..a69c71a 100644 --- a/README.md +++ b/README.md @@ -52,3 +52,9 @@ Note that the full log outputs and stored embeddings can be 5-10Gb in size (on t The unsupervised variants of GraphSAGE will output embeddings to the logging directory as described above. These embeddings can then be used in downstream machine learning applications. The `eval_scripts` directory contains examples of feeding the embeddings into simple logistic classifiers. + +#### Running on a new dataset + +To run the model on a new dataset, you need to make data files of the format described above. +To run random walks for the unsupervised model (and to generate the -walks.txt file) +you can use the `run_walks` function in `graphsage.utils`.