cmaRs: A powerful predictive data mining package in R

Date

2023-12-01

Author

Yerlikaya-Özkurt, Fatma
Yazıcı, Ceyda
Batmaz, İnci

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

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

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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85174703053&origin=inward
https://hdl.handle.net/11511/106249

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Department of Statistics, Article