An embedded and charset-unspecified text was scrubbed... Name: not available URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20090226/50aa4661/attachment-0001.pl>
Random Forest confusion matrix
2 messages · Li GUO, Gabor Grothendieck
randomForest output is based on predict(iris.rf) whereas the code shown below uses predict(iris.rf, iris). See ?predict.randomForest for an explanation.
On Thu, Feb 26, 2009 at 11:10 AM, Li GUO <guoli84 at yahoo.com> wrote:
Dear R users, I have a question on the confusion matrix generated by function randomForest. I used the entire data set to generate the forest, for example:
print(iris.rf)
Call: ?randomForest(formula = Species ~ ., data = iris, importance = TRUE, keep.forest = TRUE) confusion ? ? ? ? ? setosa versicolor virginica class.error setosa ? ? ? ? 50 ? ? ? ? ?0 ? ? ? ? 0 ? ? ? ?0.00 versicolor ? ? ?0 ? ? ? ? 47 ? ? ? ? 3 ? ? ? ?0.06 virginica ? ? ? 0 ? ? ? ? ?3 ? ? ? ?47 ? ? ? ?0.06 then I classified the same data set with this forest:
iris.pred <- predict(iris.rf, iris) table(observed = iris[,"Species"], predicted = iris.pred)
? ? ? ? ? ?predicted observed ? ? setosa versicolor virginica ?setosa ? ? ? ? 50 ? ? ? ? ?0 ? ? ? ? 0 ?versicolor ? ? ?0 ? ? ? ? 50 ? ? ? ? 0 ?virginica ? ? ? 0 ? ? ? ? ?0 ? ? ? ?50 Why the two matrices are different? Thinks, Li ? ? ? ?[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.