beset | R Documentation |
beset
is a portmanteau of BEst subSET, which references the overall
objective of this package: to identify the best subset of variables for
a predictive model. To learn more about beset
, start with the
vignettes: browseVignettes(package = "beset")
Provide a fast and easy way to cross-validate GLMs.
Establish a common, user-friendly interface for best subset selection
that works with several model fitting functions (lm
,
glm
, and glm.nb
).
Make elastic-net regression more accessible and interpretable by
providing a wrapper to glmnet
that maintains the
same user interface as lm
and
glm
and provides informative plot and summary
methods.
beset_glm
Performs best subset selection using repeated cross-validation to find the optimal number of predictors for several families of generalized linear models.
beset_elnet
Enhances elastic-net regression with
glmnet
by 1) allowing the user to specify a model
using R's formula syntax, 2) allowing the user to simultaneously tune both
alpha and lambda using cross-validation, and 3) providing a summary output
that ranks the relative importance of the predictors that survived
shrinkage and gives some statistics indicating how well the model fits the
training data and predicts new data.
validate
An S3 object system that makes it easy to obtain cross-validated prediction stats for a previously fit model.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.