Extract predictions and MAR columns from autoMAR objects

this function can be used for autoMAR objects to generate the variable for missing variable not completely at random

predictAutoMAR(x, data, mar_var = NULL)

Arguments

x	[autoMAR object | Required] autoMAR object for which prediction is desired
data	[data.frame | Required] prediction data set to prepare the autoMAR outcomes
mar_var	[character list | Optional] list of predefined mar variables

Value

flagged variables for missing not completely at random variable

Examples

## Missing at random features
train <- heart[1 : 199, ]
test <- heart[200 : 300, ]
marobj <- autoMAR (train, aucv = 0.9, strataname = NULL, stratasize = NULL, mar_method = "glm")
#> less than or equal to one missing value coloumn found in the dataframe

## print summary in console
testobj <- predictAutoMAR(marobj, test)
#> Not found any MAR variables, please check you autoMAR object auc.features