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.
na.tree.replace(frame) na.tree.replace.all(frame)
"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.
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).
z <- tree(market.survey, na.action=na.tree.replace)