Hey, I've found that RFECV does a good job of selecting features, but that
it's quite slow. It is quicker if it's used with a fast estimator. For
example, I've found that SGDRegressor is much faster than SVR. I was
wondering any regressor is faster than SGDRegressor (for dense features).
Remember, only estimators with a coef_ attribute can be used with recursive
feature elimination.
Also, is the warm_start option relevant here? In theory, the coefficients
from an estimator fit with N features could be used for fitting an
estimator with N - 1 features. In practice though, RFE and RFECV might not
copy the coef_ array between runs.
Thanks,
Conrad
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