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Cross-Validation-Random-Forest

Using k-Fold Cross Validation to find Optimal number of trees:

I split the dataset into 10 folds for cross validation.

I then obtained cross validation results for 1:100 trees in a Random Forest Classification

I did this by nesting the 1:100 iterations of the Random Forest algorthim inside a for loop for 10 different validation sets.

Important note I am unsure why this happens, but maybe someone can explain: In order for the for-loop to work, you need to run it without the indexes (I used [j] for the fold iteration, and [i] for random forest. Just delete these, run the code first to get a single value result. Then, re-add the [i] and [j] inside the loops, and then it will work.

If you know why R works like this, let me know. Thanks!

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Using k-Fold Cross Validation to find Optimal number of trees

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