imputations {mlr} | R Documentation |
Built-in imputation methods.
Description
The built-ins are:
-
imputeConstant(const)
for imputation using a constant value, -
imputeMedian()
for imputation using the median, -
imputeMode()
for imputation using the mode, -
imputeMin(multiplier)
for imputing constant values shifted below the minimum usingmin(x) - multiplier * diff(range(x))
, -
imputeMax(multiplier)
for imputing constant values shifted above the maximum usingmax(x) + multiplier * diff(range(x))
, -
imputeNormal(mean, sd)
for imputation using normally distributed random values. Mean and standard deviation will be calculated from the data if not provided. -
imputeHist(breaks, use.mids)
for imputation using random values with probabilities calculated usingtable
orhist
. -
imputeLearner(learner, features = NULL)
for imputations using the response of a classification or regression learner.
Usage
imputeConstant(const)
imputeMedian()
imputeMean()
imputeMode()
imputeMin(multiplier = 1)
imputeMax(multiplier = 1)
imputeUniform(min = NA_real_, max = NA_real_)
imputeNormal(mu = NA_real_, sd = NA_real_)
imputeHist(breaks, use.mids = TRUE)
imputeLearner(learner, features = NULL)
Arguments
const |
(any) |
multiplier |
( |
min |
( |
max |
( |
mu |
( |
sd |
( |
breaks |
( |
use.mids |
( |
learner |
(Learner | |
features |
(character) |
See Also
Other impute:
impute()
,
makeImputeMethod()
,
makeImputeWrapper()
,
reimpute()