I've built a toy Random Forest model in
R (using the
German Credit dataset from the
caret package), exported it in
PMML 4.0 and deployed onto Hadoop, using the
Cascading Pattern library.
I've run into an issue where
Cascading Pattern scores the same data differently (in a binary classification problem) than the same model in
R. Out of 200 observations, 2 are scored differently.
Why is this? Could it be due to a difference in the implementation of Random Forests?