Description Usage Arguments Details Examples
View source: R/feature.boruta.R
The method ensures that the parameters of the feature.boruta
function are valid.
1 2 | feature.boruta.checkInputParams(target, predictors, checkNA = F,
verbose = F)
|
target |
Response vector; factor for classification, numeric vector for regression. |
predictors |
|
checkNA |
|
verbose |
|
This method analyses the target
and predictors
input variables
of the feature.boruta
function. It conducts two mandatory
checks and one optional check. The first of the two mandatory checks
evaluates whether the correct data types are used. So the target
variable should be a vector
while the predictors
variable is
supposed to be a data.frame
. As a second check it is ensured that
both variables have the same number of rows, which implies that the number of
considered observation is equal for both. If one of the checks fail,
execution will be aborted with an error explaining the reasons.
The optional check evaluates the presence of NA
values as these are
not useable for many of the Boruta classifiers. In case either target
and/or predictors
contain only one NA
a warning is issued. If
the verbose
switch is TRUE
, the error will provide a list of
predictors
columns which contain NA
values.
1 2 3 4 | KaggleHouse:::feature.boruta.checkInputParams(
target = data_train_na$SalePrice, predictors = data_train_na[-81],
checkNA = T, verbose = T
)
|
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