imputation.apply: imputation.apply - fill data gaps (NA valuse) with values...
In rzaluska/mow: R data preprocessing functions - University Project.

Description Usage Arguments Value Examples

imputation.apply - fill data gaps (NA valuse) with values computed by inputation.prepare

1	imputation.apply(data, transformation_parameters, mark_artificial_values = F)

`transformation_parameters`	- paramets obtainded from imputation.prepare function
`mark_artificial_values`	- for all columns with missing values add new column and mark artificial values in it (default False)

data with NA values set based on transformation_parameters

iris_c = iris
fil = seq(from=1, to=150, by=2)
iris_c[fil, 1:2] = NA
p = inputation.prepare(iris_c, c(1, 2),  c("average", "median"))
after1 = inputation.apply(iris_c, p)