Comments (1)
Thanks for looking into the code. It is indeed intended to use OOB predictions since insample predictions of random forests typically are badly overfitted and too close to the observed values:
library(ranger)
fit <- ranger(Sepal.Length ~ ., data = iris) # OOB R-squared: 0.8395822
insample_residuals <- iris$Sepal.Length - predict(fit, iris)$predictions
1 - var(insample_residuals) / var(iris$Sepal.Length) # Insample R-squared: 0.9546763
from missranger.
Related Issues (20)
- Replace `cat` with `message` HOT 3
- Is there any parallelization option? HOT 1
- Return OOB accuracy HOT 5
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- allow syntactically wrong colum names like "bad name"
- Initial matrix prior to iterating HOT 1
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- Multiple imputation via bootstrapping rather than predictive mean matching HOT 1
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- Parallel & progress bars HOT 2
- How to test the accuracy of predictions? HOT 1
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from missranger.