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KRLS (version 0.3-1)

Kernel-based Regularized Least Squares (KRLS)

Description

Package implements Kernel-based Regularized Least Squares (KRLS), a machine learning method to fit multidimensional functions for regression and classification problems without relying on linearity or additivity assumptions. This package is currently in alpha phase (feedback is appreciated).

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Version

Install

install.packages('KRLS')

Monthly Downloads

347

Version

0.3-1

License

GPL (>= 2)

Maintainer

Jens Hainmueller

Last Published

August 7th, 2013

Functions in KRLS (0.3-1)

krls

Kernel-based Regularized Least Squares (KRLS)
summary.krls

Summary method for Kernel-based Regularized Least Squares (KRLS) Model Fits
solveforc

Solve for Choice Coefficients in KRLS
plot.krls

Plot method for Kernel-based Regularized Least Squares (KRLS) Model Fits
predict.krls

Predict method for Kernel-based Regularized Least Squares (KRLS) Model Fits
looloss

Loss Function for Leave One Out Error
gausskernel

Gaussian Kernel Distance Computation