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In order to ensure repdoducability of experiments, it would be useful to be able to set a random seed for the computation of smoothed p-values. In particular when working with small datasets. One solution might be to pass the seed as an optional argument to WrapClassifyer/WrapRegressor.
The text was updated successfully, but these errors were encountered:
I would like to second this request. I have an issue requesting this functionality in calibrated-explanations, where we get different explanations for the same instance depending on whether we make a batch explanation of multiple instances or explain one instance at a time.
Hi,
In order to ensure repdoducability of experiments, it would be useful to be able to set a random seed for the computation of smoothed p-values. In particular when working with small datasets. One solution might be to pass the seed as an optional argument to WrapClassifyer/WrapRegressor.
The text was updated successfully, but these errors were encountered: