Cmars: a Powerful Predictive Data Mining Package in R
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Open Access Color
GOLD
Green Open Access
No
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Publicly Funded
No
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.
Description
Keywords
Conic multivariate adaptive regression splines, Nonparametric regression, Tikhonov regularization, Conic quadratic programming, Interior point method, Binary classification, Conic multivariate adaptive regression splines, QA76.75-76.765, Tikhonov regularization, Interior point method, Nonparametric regression, Computer software, Binary classification, Conic quadratic programming
Turkish CoHE Thesis Center URL
Fields of Science
0211 other engineering and technologies, 02 engineering and technology, 0101 mathematics, 01 natural sciences
Citation
WoS Q
Q2
Scopus Q
Q2

OpenCitations Citation Count
3
Source
SoftwareX
Volume
24
Issue
Start Page
101553
End Page
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CrossRef : 4
Scopus : 4
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Mendeley Readers : 5
SCOPUS™ Citations
4
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Web of Science™ Citations
3
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3
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