c(person(c("Zachary", "A."), "Mayer", role = c("aut", "cre"),
email = "zach.mayer@gmail.com"),
person(c("Jared", "E."), "Knowles", role=c("aut"),
email="jknowles@gmail.com"))
Functions for creating ensembles of caret models: caretList,
caretEnsemble, and caretStack.  caretList is a convenience function for
fitting multiple caret::train models to the same dataset. caretEnsemble will
make a linear combination of these models using greedy forward selection,
and caretStack will make linear or non-linear combinations of these models,
using a caret::train model as a meta-model.
testthat, randomForest, rpart, kernlab, nnet, e1071, ipred,
pROC, knitr, mlbench, MASS, gbm, klaR
caTools, pbapply, ggplot2, digest, plyr, grid, lattice,
gridExtra
Zachary A. Mayer [aut, cre],
Jared E. Knowles [aut]

c(person(c("Zachary", "A."), "Deane-Mayer", role = c("aut", "cre"),
email = "zach.mayer@gmail.com"),
person(c("Jared", "E."), "Knowles", role=c("aut"),
email="jknowles@gmail.com"))
Functions for creating ensembles of caret models: caretList
and caretStack.  caretList is a convenience function for fitting multiple
caret::train models to the same dataset. caretStack will make linear or
non-linear combinations of these models, using a caret::train model as a
meta-model, and caretEnsemble will make a robust linear combination of
models using a glm.
caTools, testthat, lintr, randomForest, glmnet, rpart,
kernlab, nnet, e1071, ipred, pROC, knitr, mlbench, MASS, gbm,
klaR
methods, pbapply, ggplot2, digest, plyr, lattice, gridExtra,
data.table, caret
Zachary A. Deane-Mayer [aut, cre],
Jared E. Knowles [aut]

Functions for creating ensembles of caret models: caretList()
and caretStack().  caretList() is a convenience function for fitting multiple
caret::train() models to the same dataset. caretStack() will make linear or
non-linear combinations of these models, using a caret::train() model as a
meta-model, and caretEnsemble() will make a robust linear combination of
models using a GLM.
caTools, testthat, lintr, randomForest, glmnet, rpart,
kernlab, nnet, e1071, ipred, pROC, knitr, mlbench, MASS, gbm,
klaR, rmarkdown