Cmars: a Powerful Predictive Data Mining Package in R

dc.authorscopusid 36015912400
dc.authorscopusid 49662456700
dc.authorscopusid 6506670261
dc.contributor.author Yerlikaya-oezkurt, Fatma
dc.contributor.author Yazici, Ceyda
dc.contributor.author Batmaz, Inci
dc.contributor.other Industrial Engineering
dc.date.accessioned 2024-07-05T15:22:14Z
dc.date.available 2024-07-05T15:22:14Z
dc.date.issued 2023
dc.department Atılım University en_US
dc.department-temp [Yerlikaya-oezkurt, Fatma] Atilim Univ, Dept Ind Engn, Ankara, Turkiye; [Yazici, Ceyda] TED Univ, Dept Math, Ankara, Turkiye; [Batmaz, Inci] Middle East Tech Univ, Dept Stat, Ankara, Turkiye en_US
dc.description.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 MOSEK through the package Rmosek. en_US
dc.identifier.citationcount 1
dc.identifier.doi 10.1016/j.softx.2023.101553
dc.identifier.issn 2352-7110
dc.identifier.scopus 2-s2.0-85174703053
dc.identifier.uri https://doi.org/10.1016/j.softx.2023.101553
dc.identifier.uri https://hdl.handle.net/20.500.14411/2152
dc.identifier.volume 24 en_US
dc.identifier.wos WOS:001101634100001
dc.identifier.wosquality Q2
dc.institutionauthor Yerlikaya Özkurt, Fatma
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 3
dc.subject Conic multivariate adaptive regression splines en_US
dc.subject Nonparametric regression en_US
dc.subject Tikhonov regularization en_US
dc.subject Conic quadratic programming en_US
dc.subject Interior point method en_US
dc.subject Binary classification en_US
dc.title Cmars: a Powerful Predictive Data Mining Package in R en_US
dc.type Article en_US
dc.wos.citedbyCount 2
dspace.entity.type Publication
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