KRLS swMATH ID: 23167 Software Authors: Hainmueller, Jens; Hazlett, Chad Description: R package KRLS: Kernel-Based Regularized Least Squares. Package implements Kernel-based Regularized Least Squares (KRLS), a machine learning method to fit multidimensional functions y=f(x) for regression and classification problems without relying on linearity or additivity assumptions. KRLS finds the best fitting function by minimizing the squared loss of a Tikhonov regularization problem, using Gaussian kernels as radial basis functions. For further details see Hainmueller and Hazlett (2014). Homepage: https://cran.r-project.org/web/packages/KRLS/index.html Source Code: https://github.com/cran/KRLS Dependencies: R Keywords: machine learning; regression; classification; prediction; Stata; R; Journal of Statistical Software; R package Related Software: R; KSPM; mgcv; coxme; np; nlme; e1071; SPA3G; SKAT; adegenet; CompQuadForm; lme4; DEoptim; Stata; KernSmooth Cited in: 1 Document Cited by 3 Authors 1 Kim, Inyoung 1 Lee, Kyeongeun 1 Nizeyimana, Pacifique Cited in 1 Serial 1 Journal of the Korean Statistical Society Cited in 1 Field 1 Statistics (62-XX) Citations by Year