cmaRs: A powerful predictive data mining package in R

Abstract

Conic Multivariate Adaptive Regression Splines (CMARS) is a very successful method for modeling nonlinear structures in high-dimensional data. It is based on MARS algorithm and utilizes Tikhonov regularization and Conic Quadratic Optimization (CQO). In this paper, the open-source R package, cmaRs, built to construct CMARS models for prediction and binary classification is presented with illustrative applications. Also, the CMARS algorithm is provided in both pseudo and R code. Note here that cmaRs package provides a good example for a challenging implementation of CQO based on MOSEK solver in R environment by linking R to MOSEK through the package Rmosek.

Keywords

• Conic multivariate adaptive regression splines
• Nonparametric regression
• Tikhonov regularization
• Conic quadratic programming
• Interior point method
• Binary classification