carsAlgo
Competitive Adaptive Reweighted Sampling (CARS) Algorithm
Implements Competitive Adaptive Reweighted Sampling (CARS) algorithm for variable selection from high-dimensional dataset using Partial Least Squares (PLS) regression models. CARS algorithm iteratively applies the Monte Carlo sub-sampling and exponential variable elimination techniques to identify/select the most informative variables/features subjected to minimal cross-validated RMSE score. The implementation of CARS algorithm is inspired from the work of Li et al. (2009) <doi:10.1016/j.aca.2009.06.046>. This algorithm is widely applied in near-infrared (NIR), mid-infrared (MIR), hyperspectral chemometrics areas, etc.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.5.0 |
rolling source/ R- | carsAlgo_0.5.0.tar.gz |
10.0 KiB |
0.5.0 |
rolling linux/jammy R-4.5 | carsAlgo_0.5.0.tar.gz |
40.2 KiB |
0.5.0 |
latest source/ R- | carsAlgo_0.5.0.tar.gz |
10.0 KiB |
0.5.0 |
latest linux/jammy R-4.5 | carsAlgo_0.5.0.tar.gz |
40.2 KiB |
0.5.0 |
2026-04-23 source/ R- | carsAlgo_0.5.0.tar.gz |
10.0 KiB |