Description Usage Arguments Details Examples
Generate SAS DATA step code to predict the values of a random forest from the party package.
1 | cforest2sas(fit, name = "prediction", drop = TRUE)
|
fit |
a random forest trained using |
name |
the name of the variable in which to store the prediction |
drop |
whether to drop the variables for the individual trees |
Unordered factors are supported, while ordered factors and missing values are not supported.
cforest2sas
averages the predictions of the trees like
randomForest
, while cforest
averages observation weights.
1 2 3 4 5 | require(party)
iris.ct <- cforest(Species ~ .,data = iris,
controls = cforest_unbiased(ntree=5, mtry=2))
iris.sas <- cforest2sas(iris.ct)
cat(iris.sas, file="iris.sas")
|
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