mlxtend.evaluate for corrected resampled t-test from Nadeau's paper
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Description
Hi,
Thanks for your contribution. I am interested to know if you have implemented the corrected resampled t-test from Nadeau's paper https://link.springer.com/article/10.1023%2FA%3A1024068626366. As you have implemented the resampled t-test and 5x2cv paired t test. That would be great if you include this evaluation procedure.
Actually, What I did for my CV is to split my data into 250 times with a stratifiedShuflleSplit, then for each iteration, for the training dataset (0.8), I did 10-fold to find the hyper parameters and then performance of my classier was measured using the testing dataset.
Any idea to use the corrected resampled t-test for my two classifiers????
Thanks in advance
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Research direction
Start by reviewing the existing resampled t-test and 5x2cv paired t-test implementations, then compare the requested corrected resampled t-test with Nadeau's paper. The issue does not name files or tests; done would require a defined API, implementation, and tests demonstrating the corrected procedure.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100