get_learners(
lrn_ids,
tuneLength = 20,
inner = mlr::makeResampleDesc("Holdout", stratify = TRUE),
iters = 5,
prob = FALSE,
smote_data,
mes,
info
)
Arguments
lrn_ids |
character , list of mlr learner idenfitiers
|
tuneLength |
numeric , defines the granularity of the discrete tuning grid
|
inner |
resampleDesc from mlr , the inner folds of the nested resampling
|
iters |
numeric , the number of iteration for the random discrete tuning
|
prob |
logical , controls the type of output, if TRUE probabilities, if FALSE response
|
smote_data |
a named list with two elements data and labels , if smote_data is a data.frame it is cast into the expected list format |
mes |
mlr list of measure to compute while tuning, the learner are tuning against the first element
|
info |
logical , controls the amount of information printed when tuning
|