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Users might reach for epi_cor() for feature selection. This might be okay to judge whether something seems anywhere plausible for use at all, but for judging exact/relative usefulness it's not the best...
It doesn't provide a one-number summary of usefulness per signal-lag. (Also applies to even the anywhere-plausible judgment.)
It doesn't compare apples to apples across signal-lags with different availability.
It is not tailored to the evaluation metric of whatever model is actually going to be fit.
Selection and regularization should probably be handled by a modeling package, not by ad-hoc code atop an EDA utility.
We should address the points above and/or add appropriate cautions in docs.
The text was updated successfully, but these errors were encountered:
Users might reach for
epi_cor()
for feature selection. This might be okay to judge whether something seems anywhere plausible for use at all, but for judging exact/relative usefulness it's not the best...We should address the points above and/or add appropriate cautions in docs.
The text was updated successfully, but these errors were encountered: