Off topic.
But see here:
https://stats.stackexchange.com/questions/61405/random-forest-and-prediction
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sat, Jan 12, 2019 at 9:56 AM Witold E Wolski <wewol...@gmail.com> wrote:
> Hello,
>
> I am just not sure what the predict.RandomForest function is doing...
> I confused.
>
> I would expect the predictions for these 2 function calls to predict the
> same:
> ```{r}
> diachp.rf <- randomForest(quality~.,data=data,ntree=50, importance=TRUE)
>
> ypred_oob <- predict(diachp.rf)
> dataX <- data %>% select(-quality) # remove response.
> ypred <- predict( diachp.rf, dataX )
>
> ypred_oob == ypred
> ```
> These are both out of bag predictions but ypred and ypred_oob are
> actually they are very different.
>
> > table(ypred_oob , data$quality)
>
> ypred_oob 0 1
> 0 1324 346
> 1 493 2837
> > table(ypred , data$quality)
>
> ypred 0 1
> 0 1817 0
> 1 0 3183
>
> What I find even more disturbing is that 100% accuracy for ypred.
> Would you agree that this is rather unexpected?
>
> regards
> Witek
> --
> Witold Eryk Wolski
>
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