defModel: Interface for defining models
In osofr/GriDiSL: Discrete Super Learner with Grid-Search for Longitudinal Data

Specify either a single model or a grid of multple models by invoking the optional argument param_grid.

defModel(estimator, x, search_criteria, param_grid, ...)

## S3 method for class 'ModelStack'
model1 + model2

`estimator`	A character string name of package and estimator (algorithm) name, separated by "__".
`x`	A vector containing the subset of the names of the predictor variables to use in building this particular learner or grid. This argument can be used to over-ride the values of `x` provided to `fit` function. As such, the names supplied here must always be a subset of the names specified to `fit`. When this argument is missing (default) the column names provided to `fit` are used as predictors in building this model / grid.
`search_criteria`	Search criteria
`param_grid`	Named list of model hyper parameters (optional). Each named item defines either a fixed model parameter value or a vector of possible values. In the latter case this function call would define a grid (ensemble) of models. Each model in the ensemble corresponds by a particular fixed parameter value.
`...`	Additional modeling parameters to be passed on directly to the modeling function.
`model1`	An object returned by a call to `defModel` function.
`model2`	An object returned by a call to `defModel` function.