impute {mlr} | R Documentation |
Impute and re-impute data
Description
Allows imputation of missing feature values through various techniques. Note that you have the possibility to re-impute a data set in the same way as the imputation was performed during training. This especially comes in handy during resampling when one wants to perform the same imputation on the test set as on the training set.
The function impute
performs the imputation on a data set and returns,
alongside with the imputed data set, an “ImputationDesc” object
which can contain “learned” coefficients and helpful data.
It can then be passed together with a new data set to reimpute.
The imputation techniques can be specified for certain features or for feature classes, see function arguments.
You can either provide an arbitrary object, use a built-in imputation method listed under imputations or create one yourself using makeImputeMethod.
Usage
impute(
obj,
target = character(0L),
classes = list(),
cols = list(),
dummy.classes = character(0L),
dummy.cols = character(0L),
dummy.type = "factor",
force.dummies = FALSE,
impute.new.levels = TRUE,
recode.factor.levels = TRUE
)
Arguments
obj |
(data.frame | Task) |
target |
(character) |
classes |
(named list) |
cols |
(named list) |
dummy.classes |
(character) |
dummy.cols |
(character) |
dummy.type |
( |
force.dummies |
( |
impute.new.levels |
( |
recode.factor.levels |
( |
Details
The description object contains these slots
target (character): See argument
features (character): Feature names (column names of
data
)classes (character): Feature classes (storage type of
data
)lvls (named list): Mapping of column names of factor features to their levels, including newly created ones during imputation
impute (named list): Mapping of column names to imputation functions
dummies (named list): Mapping of column names to imputation functions
impute.new.levels (
logical(1)
): See argumentrecode.factor.levels (
logical(1)
): See argument
Value
(list)
data (data.frame): Imputed data.
desc (
ImputationDesc
): Description object.
See Also
Other impute:
imputations
,
makeImputeMethod()
,
makeImputeWrapper()
,
reimpute()
Examples
df = data.frame(x = c(1, 1, NA), y = factor(c("a", "a", "b")), z = 1:3)
imputed = impute(df, target = character(0), cols = list(x = 99, y = imputeMode()))
print(imputed$data)
reimpute(data.frame(x = NA_real_), imputed$desc)