
- Surrogate predicate information;
- Missing value strategy (default child strategy);
- Regression trees.
The example below shows how to train a classification tree using the audit dataset provided by Togaware (thanks to Graham Williams).
library(XML);
library(rpart);
library(pmml);
audit <- read.csv(file("http://rattle.togaware.com/audit.csv"));
audit.rpart <- rpart(as.factor(TARGET_Adjusted) ~ ., data=audit[,c(2:10,13)]);
saveXML(pmml(audit.rpart), "AuditTree.xml");
BTW, any models you build in rpart and export using the PMML package can be uploaded directly into ADAPA for scoring.
Also, feel free to watch the video below (featuring this posting).
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