mlr3classifier — mlr3classification • subtyper

build a mlr3 classification model

mlr3classification(
  dfin,
  tcols,
  learnerName,
  partrate = 0.8,
  dup_size = 0,
  balancing = "smote",
  subjectIDs = NULL,
  verbose = TRUE
)

Arguments

dfin: dataframe input
tcols: columns for the prediction task - first is the target outcome
learnerName: which mlr3 learner to instantiate
partrate: partition ratio for the training 0.8 equals 80 percent train 20 test
dup_size: integer for over/under/smote sampling
balancing: string over, under, smote, rwo, mwmote, racog, none are the options
subjectIDs: unique IDs per subject; aids with repeated measurement data by ensuring subjects exist in uniquely in either train or test
verbose: boolean

dataframe with task, learner, accuracy and balanced accuracy

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