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| author | YurenHao0426 <blackhao0426@gmail.com> | 2026-02-24 08:40:49 +0000 |
|---|---|---|
| committer | YurenHao0426 <blackhao0426@gmail.com> | 2026-02-24 08:40:49 +0000 |
| commit | 8f63cf9f41bbdb8d55cd4679872d2b4ae2129324 (patch) | |
| tree | ab5c95888849e854f2346db856c7edece7c8b8a7 /CLAUDE.md | |
EC-SBM community detection analysis: full pipeline and writeup
Implement community detection on 3 EC-SBM networks (polblogs, topology,
internet_as) using 5 methods (Leiden-Mod, Leiden-CPM at 0.1 and 0.01,
Infomap, graph-tool SBM). Compute AMI/ARI/NMI accuracy, cluster statistics,
and generate figures and LaTeX report.
Diffstat (limited to 'CLAUDE.md')
| -rw-r--r-- | CLAUDE.md | 2 |
1 files changed, 2 insertions, 0 deletions
diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 0000000..4763a31 --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,2 @@ +This assignment will involve data analysis. You will apply community detection methods to EC-SBM synthetic networks, which come with ground truth communities; this will allow you to evaluate accuracy. You will report empirical statistics about the communities you obtain (e.g., distribution of community sizes and edge densities, mixing parameters, percentage of nodes not in any cluster of size at least two). You will also report accuracy using at a minimum AMI, ARI, and NMI. You will also write up your study with details sufficient to be reproducible and with commentary about what you learned. See this page for details. +https://tandy.cs.illinois.edu/598-data-analysis-hw.html |