node2vecR: Algorithmic Framework for Representational Learning on Graphs

In node2vec: Algorithmic Framework for Representational Learning on Graphs

Description

Algorithmic Framework for Representational Learning on Graphs

Usage

node2vecR(
  data,
  p = NULL,
  q = NULL,
  directed = NULL,
  num_walks = NULL,
  walk_length = NULL,
  dim = NULL
)

Arguments

data	input data for edges consisting of at least two columns of data and if there are weights,it must be in the third column.
p	return parameter.Default to 1.
q	in-out parameter.Default to 1.
directed	the network is directed or undirected.Default to undirected.
num_walks	number of walks per node.Default to 10.
walk_length	number of nodes in each walk.Default to 80.
dim	embedding dimensions.Default to 128.

Value

embedding results for each node

Examples

#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)

node2vec documentation built on Jan. 16, 2021, 5:30 p.m.