KRLS: Kernel-based Regularized Least squares (KRLS)

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).

Install the latest version of this package by entering the following in R:
AuthorJens Hainmueller (Stanford) Chad Hazlett (UCLA)
Date of publication2014-05-21 21:21:47
MaintainerJens Hainmueller <>
LicenseGPL (>= 2)

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