For a general overview on how to integrate a learning algorithm into mlr's system, please read the section in the online tutorial: http://mlr-org.github.io/mlr-tutorial/release/html/create_learner/index.html
To see all possible properties of a learner, go to: LearnerProperties
.
makeRLearner()
makeRLearnerClassif(cl, package, par.set, par.vals = list(), properties = character(0L), name = cl, short.name = cl, note = "", class.weights.param = NULL)
makeRLearnerMultilabel(cl, package, par.set, par.vals = list(), properties = character(0L), name = cl, short.name = cl, note = "")
makeRLearnerRegr(cl, package, par.set, par.vals = list(), properties = character(0L), name = cl, short.name = cl, note = "")
makeRLearnerSurv(cl, package, par.set, par.vals = list(), properties = character(0L), name = cl, short.name = cl, note = "")
makeRLearnerCluster(cl, package, par.set, par.vals = list(), properties = character(0L), name = cl, short.name = cl, note = "")
makeRLearnerCostSens(cl, package, par.set, par.vals = list(), properties = character(0L), name = cl, short.name = cl, note = "")
character(1)
]
Class of learner. By convention, all classification learners
start with classif., all regression learners with
regr., all survival learners start with surv.,
all clustering learners with cluster., and all multilabel
classification learners start with multilabel..
A list of all integrated learners is available on the
learners
help page.character
]
Package(s) to load for the implementation of the learner.ParamSet
]
Parameter set of (hyper)parameters and their constraints.
Dependent parameters with a requires
field must use quote
and not
expression
to define it.list
]
Always set hyperparameters to these values when the object is constructed.
Useful when default values are missing in the underlying function.
The values can later be overwritten when the user sets hyperparameters.
Default is empty list.character
]
Set of learner properties. See above.
Default is character(0)
.character(1)
]
Meaningful name for learner.
Default is id
.character(1)
]
Short name for learner.
Should only be a few characters so it can be used in plots and tables.
Default is id
.character(1)
]
Additional notes regarding the learner and its integration in mlr.
Default is .character(1)
]
Name of the parameter, which can be used for providing class weights.RLearner
]. The specific subclass is one of RLearnerClassif
,
RLearnerCluster
, RLearnerMultilabel
,
RLearnerRegr
, RLearnerSurv
.