[R] randomForest out of bag prediction

[Michael Mayer]

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.

Gesendet von Mail für Windows 10

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

______________________________________________
R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.


	[[alternative HTML version deleted]]