[R] randomForest out of bag prediction

Michael Mayer m@yermich@el79 @ending from gm@il@com
Sat Jan 12 19:16:18 CET 2019


predict(diachp.rf, dataX) returns the in-sample predictions, not the OOB predictions. The response variable «quality» is only used during model fit, not during prediction. 

Since in-sample predictions of random forests are typically grossly overfitted by construction, extremely high accuracies are not unexpected.

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Von: Witold E Wolski
Gesendet: Samstag, 12. Januar 2019 18:56
An: r-help using r-project.org
Betreff: [R] randomForest out of bag prediction

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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