RECA
Relevant Component Analysis for Supervised Distance Metric Learning
Relevant Component Analysis (RCA) tries to find a linear transformation of the feature space such that the effect of irrelevant variability is reduced in the transformed space.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.7.1 |
rolling linux/jammy R-4.5 | RECA_1.7.1.tar.gz |
49.7 KiB |
1.7.1 |
rolling linux/noble R-4.5 | RECA_1.7.1.tar.gz |
49.6 KiB |
1.7.1 |
rolling source/ R- | RECA_1.7.1.tar.gz |
40.9 KiB |
1.7.1 |
latest linux/jammy R-4.5 | RECA_1.7.1.tar.gz |
49.7 KiB |
1.7.1 |
latest linux/noble R-4.5 | RECA_1.7.1.tar.gz |
49.6 KiB |
1.7.1 |
latest source/ R- | RECA_1.7.1.tar.gz |
40.9 KiB |
1.7.1 |
2026-04-26 source/ R- | RECA_1.7.1.tar.gz |
40.9 KiB |
1.7.1 |
2026-04-23 source/ R- | RECA_1.7.1.tar.gz |
40.9 KiB |
1.7.1 |
2026-04-09 windows/windows R-4.5 | RECA_1.7.1.zip |
52.2 KiB |
1.7 |
2025-04-20 source/ R- | RECA_1.7.tar.gz |
16.9 KiB |