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.