Cmars: a Powerful Predictive Data Mining Package in R

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Date

2023

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Publisher

Elsevier

Open Access Color

GOLD

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No

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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

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Fields of Science

0211 other engineering and technologies, 02 engineering and technology, 0101 mathematics, 01 natural sciences

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WoS Q

Q2

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Q2
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3

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SoftwareX

Volume

24

Issue

Start Page

101553

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CrossRef : 4

Scopus : 4

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4

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3

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3

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