cforest2sas: Export a random forest to SAS
In az0/mlmeta: Machine Learning Metaprogramming

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 `cforest`
`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.

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")