**For Large Graphs** : Increase the size of hash table in NERD.h (look for **hash_table_size**) accordingly.

> **For Large Graphs** : Increase the size of hash table in NERD.h (look for **hash_table_size**) accordingly.

The algorithm expects a **directed weighted edgelist**. If your graph is unweighted, please add 1 as weight for all edges. For undirected graphs, please add 2 edges ( in both directions) corresponding to each edge.

For bipartite undirected graphs, one can treat edges directed from the left set to the right set and doubling of edges is not required.

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@@ -45,9 +51,9 @@ Parameters for training:

-inputvertex : if set 0 Use the first vertex in the walk sample as the input word otherwise use the middle vertex in the sample walk (default is 0)

**Evaluation**: The embeddings are evaluated for three tasks : Node Classification, Link Prediction and Graph Reconstruction. Respective evaluation scripts are evaluation/ multilabel_class_cv.py,

>**Evaluation**: The embeddings are evaluated for three tasks : Node Classification, Link Prediction and Graph Reconstruction. Respective evaluation scripts are evaluation/ multilabel_class_cv.py,