Clustering evaluation metrics

The RI, NMI and conductance metrics are implemented using Cython. Note that conductance is implemented for unweighted and undirected graph. There are example graph and community files under the data/ directory.

Dependencies

• Cython
• numpy

Compile

The code works for both python2 and python3

git clone https://github.com/alamages/cls-metrics.git
cd cls-metrics
make

Data

The code supports undirected unweighted graphs. The input graph must be provided in this format:

[node_id] [neighbor_id1] [neighbor_id2] ....

The node ids must appear in an increasing sequence starting from index 1 up to n (where n is the number of nodes). Same with the neighbor ids.

Same for the community/cluster files the node ids must appear in an increasing sequence, the format is:

[node_id] [community_id]

Examples of input files can be found under the data/ folder.

Examples

# to print the scripts' arguments use -h/--help argument:
./conductance.py -h

# conductance:
./conductance.py -g data/graph -c data/clusters

# ri and nmi metrics:
./ri_nmi.py -g data/community -c data/clusters