Package: customizedTraining
Type: Package
Title: Customized Training for Lasso and Elastic-Net Regularized
        Generalized Linear Models
Version: 1.3
Date: 2024-12-23
Authors@R: c(person(given = "Scott",
                    family = "Powers",
                    role = c("aut", "cre"),
                    email = "saberpowers@gmail.com"),
             person(given = "Trevor",
                    family = "Hastie",
                    role = "aut"),
             person(given = "Robert",
                    family = "Tibshirani",
                    role = "aut"))
Maintainer: Scott Powers <saberpowers@gmail.com>
Imports: FNN, glmnet
Description: Customized training is a simple technique for transductive
        learning, when the test covariates are known at the time of
        training. The method identifies a subset of the training set to
        serve as the training set for each of a few identified subsets
        in the training set. This package implements customized
        training for the glmnet() and cv.glmnet() functions.
License: GPL-2
Encoding: UTF-8
RoxygenNote: 7.3.2
Repository: https://saberpowers.r-universe.dev
Date/Publication: 2024-12-24 01:27:43 UTC
RemoteUrl: https://github.com/saberpowers/customizedtraining
RemoteRef: HEAD
RemoteSha: edb4170a20909f4acd72d6ed33ef13b6fc6778fa
NeedsCompilation: no
Packaged: 2026-06-19 11:13:13 UTC; root
Author: Scott Powers [aut, cre],
  Trevor Hastie [aut],
  Robert Tibshirani [aut]