makePreprocWrapper: Fuse learner with preprocessing.
In shuodata/mlr-master: Machine Learning in R

Description Usage Arguments Value See Also

Fuses a base learner with a preprocessing method. Creates a learner object, which can be used like any other learner object, but which internally preprocesses the data as requested. If the train or predict function is called on data / a task, the preprocessing is always performed automatically.

1 2	makePreprocWrapper(learner, train, predict, par.set = makeParamSet(), par.vals = list())

`learner`	[`Learner` \| `character(1)`] The learner. If you pass a string the learner will be created via `makeLearner`.
`train`	[`function(data, target, args)`] Function to preprocess the data before training. `target` is a string and denotes the target variable in `data`. `args` is a list of further arguments and parameters to influence the preprocessing. Must return a `list(data, control)`, where `data` is the preprocessed data and `control` stores all information necessary to do the preprocessing before predictions.
`predict`	[`function(data, target, args, control)`] Function to preprocess the data before prediction. `target` is a string and denotes the target variable in `data`. `args` are the args that were passed to `train`. `control` is the object you returned in `train`. Must return the processed data.
`par.set`	[`ParamSet`] Parameter set of `LearnerParam` objects to describe the parameters in `args`. Default is empty set.
`par.vals`	[`list`] Named list of default values for params in `args` respectively `par.set`. Default is empty list.