Per #11142, this PR adds logic to account for sample weights when computing the oobError during training in rtrees.

Open questions:

• Should oobError be moved outside the loop to ensure it's computed for the forest, rather than being reset per tree? That would also require changing the termination condition (maybe using a local error accumulator which as added to oobError).
• Should we be averaging over n_oob?

This also addresses #4431, as it makes OOB error accessible.

Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

• I agree to contribute to the project under Apache 2 License.
• To the best of my knowledge, the proposed patch is not based on a code under GPL or other license that is incompatible with OpenCV
• The PR is proposed to proper branch
• There is reference to original bug report and related work
• There is accuracy test, performance test and test data in opencv_extra repository, if applicable
  Patch to opencv_extra has the same branch name.
• The feature is well documented and sample code can be built with the project CMake