KODAMA
Knowledge Discovery by Accuracy Maximization
A self-guided, weakly supervised learning algorithm for feature extraction from noisy and high-dimensional data. It facilitates the identification of patterns that reflect underlying group structures across all samples in a dataset. The method incorporates a novel strategy to integrate spatial information, improving the clarity of results in spatially resolved data.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
3.3 |
rolling linux/jammy R-4.5 | KODAMA_3.3.tar.gz |
2.6 MiB |
3.3 |
rolling linux/noble R-4.5 | KODAMA_3.3.tar.gz |
2.7 MiB |
3.3 |
rolling source/ R- | KODAMA_3.3.tar.gz |
3.3 MiB |
3.3 |
latest linux/jammy R-4.5 | KODAMA_3.3.tar.gz |
2.6 MiB |
3.3 |
latest linux/noble R-4.5 | KODAMA_3.3.tar.gz |
2.7 MiB |
3.3 |
latest source/ R- | KODAMA_3.3.tar.gz |
3.3 MiB |
3.3 |
2026-04-26 source/ R- | KODAMA_3.3.tar.gz |
3.3 MiB |
3.3 |
2026-04-23 source/ R- | KODAMA_3.3.tar.gz |
3.3 MiB |
3.3 |
2026-04-09 windows/windows R-4.5 | KODAMA_3.3.zip |
3.0 MiB |
2.4.1 |
2025-04-20 source/ R- | KODAMA_2.4.1.tar.gz |
3.2 MiB |