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Algorithmic Framework for Representational Learning on Graphs
node2vecR( data, p = NULL, q = NULL, directed = NULL, num_walks = NULL, walk_length = NULL, dim = NULL )
input data for edges consisting of at least two columns of data and if there are weights,it must be in the third column.
return parameter.Default to 1.
in-out parameter.Default to 1.
the network is directed or undirected.Default to undirected.
number of walks per node.Default to 10.
number of nodes in each walk.Default to 80.
embedding dimensions.Default to 128.
embedding results for each node
# NOT RUN { #Parameters can be customized as needed data(gene_edges) use_data<-gene_edges emb<-node2vecR(use_data,p=2,q=1,num_walks=5,walk_length=5,dim=10) # }
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