Adds a new level called "NA" to any discrete predictor in a data frame that
contains NAs. na.tree.replace stops if any continuous (numeric) predictor
contains an NA. na.tree.replace.all will quantize numeric predictors and
create a factor with a level for the missing values.
USAGE:
na.tree.replace(frame)
na.tree.replace.all(frame)
REQUIRED ARGUMENTS:
frame:
data frame used to grow a tree.
VALUE:
data frame such that a new level named "NA" is added to any discrete
predictor in frame with NAs. In the case of na.tree.replace.all,
all predictors having NAs are changed in an analogous manner.
DETAILS:
This function is used via the na.action argument to tree.
The use of na.tree.replace.all for continuous
variables with missing values might be risky. These continuous predictors
are replaced by factors based on their quartiles. This migh be a good exploratory step but it raises a problem if used in predictions.
If the variable has
missing values in only one of the fitted or the new datasets, the values used
may turn out completely incompatible (factor vs. numeric).
EXAMPLES:
z <- tree(market.survey, na.action=na.tree.replace)