SYNTHETIC contains the following comma separated text files:

n: total number of nodes
m: total number of edges
N: number of graphs


*.node_attrs (n lines) 
	matrix of node attributes,
	the comma seperated values in the i-th line is the attribute vector of the node with node_id i

*.node_labels (n lines)
	column vector of node labels,
	the value in the i-th line corresponds to the node with node_id i

*.edges (m lines) 
	sparse (block diagonal) adjacency matrix for all graphs,
	each line corresponds to (row, col) resp. (node_id, node_id)

*.graph_labels (N lines)
	class labels for all graphs in the dataset,
	the value in the i-th line is the class label of the graph with graph_id i

*.graph_idx (n lines)
	column vector of graph identifiers for all nodes of all graphs,
	the value in the i-th line is the graph_id of the node with node_id i

--- Description --- 

SYNTHETIC is a set of synthetic graphs based on a random graph G
with 100 nodes and 196 edges, whose nodes are endowed with normally distributed scalar attributes
sampled from N (0, 1). Two classes A and B each with 150 attributed graphs were generated from
G by permuting node attributes. Each graph in A was generated by permuting 10 node attributes, 
and each graph in B was generated by permuting 5 node attributes, after which noise from 
N (0, 0.452) was added to every node attribute in every graph.




Please cite the following if you use the data:

@inproceedings{networkrepo,
    title = {The Network Data Repository with Interactive Graph Analytics and Visualization},
    author={Ryan A. Rossi and Nesreen K. Ahmed},
    booktitle = {AAAI},
    url={http://networkrepository.com},
    year={2015}
}

