caretEnsemble (version 4.0.1)

caretList: Create a list of several train models from the caret package

Description

Build a list of train objects suitable for ensembling using the caretStack function.

Usage

caretList(
  ...,
  trControl = NULL,
  methodList = NULL,
  tuneList = NULL,
  metric = NULL,
  continue_on_fail = FALSE,
  trim = TRUE
)

Value

A list of train objects. If the model fails to build, it is dropped from the list.

Arguments

...

arguments to pass to train. Don't use the formula interface, its slower and buggier compared to the X, y interface. Use a data.table for X. Particularly if you have a large dataset and/or many models, using a data.table will avoid unnecessary copies of your data and can save a lot of time and RAM. These arguments will determine which train method gets dispatched.

trControl

a trainControl object. If NULL, will use defaultControl.

methodList

optional, a character vector of caret models to ensemble. One of methodList or tuneList must be specified.

tuneList

optional, a NAMED list of caretModelSpec objects. This much more flexible than methodList and allows the specification of model-specific parameters (e.g. passing trace=FALSE to nnet)

metric

a string, the metric to optimize for. If NULL, we will choose a good one.

continue_on_fail

logical, should a valid caretList be returned that excludes models that fail, default is FALSE

trim

logical should the train models be trimmed to save memory and speed up stacking

Examples

caretList(
  Sepal.Length ~ Sepal.Width,
  head(iris, 50),
  methodList = c("glm", "lm"),
  tuneList = list(
    nnet = caretModelSpec(method = "nnet", trace = FALSE, tuneLength = 1)
  )
)