Cmars: a Powerful Predictive Data Mining Package in R
| dc.contributor.author | Yerlikaya-oezkurt, Fatma | |
| dc.contributor.author | Yazici, Ceyda | |
| dc.contributor.author | Batmaz, Inci | |
| dc.contributor.other | Industrial Engineering | |
| dc.contributor.other | 06. School Of Engineering | |
| dc.contributor.other | 01. Atılım University | |
| dc.date.accessioned | 2024-07-05T15:22:14Z | |
| dc.date.available | 2024-07-05T15:22:14Z | |
| dc.date.issued | 2023 | |
| 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.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.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.relation.ispartof | SoftwareX | |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| 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 |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Yerlikaya Özkurt, Fatma | |
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| gdc.coar.access | open access | |
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| gdc.description.department | Atılım University | en_US |
| gdc.description.departmenttemp | [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 |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.startpage | 101553 | |
| gdc.description.volume | 24 | en_US |
| gdc.description.wosquality | Q2 | |
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| gdc.oaire.keywords | Conic multivariate adaptive regression splines | |
| gdc.oaire.keywords | QA76.75-76.765 | |
| gdc.oaire.keywords | Tikhonov regularization | |
| gdc.oaire.keywords | Interior point method | |
| gdc.oaire.keywords | Nonparametric regression | |
| gdc.oaire.keywords | Computer software | |
| gdc.oaire.keywords | Binary classification | |
| gdc.oaire.keywords | Conic quadratic programming | |
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