HRTs enable you to perform feature selection with statistical guarantees. Specifically, if you fit any predictive model, HRTs can use its performance on the test data under various randomizations to assign a valid (or conservative) p-value to each feature. The p-value corresponds to an estimate of the outcome of a conditional independence test, testing if feature X_j is independent of the response y given the remaining variables X_{-j}.

Clone the repo and run python setup.py install

Coming soon... see examples/olfaction/main.py until then.