[R] Random Forest confusion matrix

[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
>
>
>
>
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>
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