Butterfly similarity network
Dataset information
This is a butterfly similarity network. Nodes represent butterflies (organisms) and edges represent visual similarities between the organisms. Visual similarities are calculated using butterfly images.
| Dataset statistics | |
|---|---|
| Nodes | 832 |
| Edges | 86528 |
| Nodes in largest SCC | 832 |
| Fraction of nodes in largest SCC | 1.000000 |
| Edges in largest SCC | 86528 |
| Fraction of edges in largest SCC | 1.000000 |
| Average clustering coefficient | 0.595439 |
| Number of triangles | 14774008 |
| Fraction of closed triangles | 0.301405 |
| Diameter (longest shortest path) | 3 |
| 90-percentile effective diameter | 1.918374 |
The information is extracted from the Leeds butterfly fine-grained species image dataset. Network statistics are calculated on edges with weights above the 75-th percentile.
References
- Network enhancement as a general method to denoise weighted biological networks. Bo Wang, Armin Pourshafeie, Marinka Zitnik, Junjie Zhu, Carlos D. Bustamante, Serafim Batzoglou, and Jure Leskovec. Nature Communications. 2018.
- Learning models for object recognition from natural language descriptions. Wang, J. et al. Proceedings of British Machine Vision Conference. 2009.
Files
| File | Size | Description |
|---|---|---|
| SS-Butterfly_labels.tsv.gz | 17MB | Butterfly species (labels) |
| SS-Butterfly_weights.tsv.gz | 17MB | Butterfly similarity network (weighted edgelist) |