Adversarial test: simple way to know if your train data and test data are similar
We combine our train and test data, labeling them 0 for the training data and 1 for the test data, mix them up, then see if we are able to correctly re-identify them using a binary classifier.
If a classifier can identify whether a sample comes from train or test data set, we know that there's at least one feature in your data is shifted; use feature importance methods to point out the shifted feature(s)
Get Started and Documentation
To install from pip:
pip install adversarial-test
Code example:
- Using adversarial test with category features
- See more usages in notebooks directory
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Release files for adversarial-test 0.1.4
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