Comments (1)
This issue could theoretically be closed, as logreg_fit
and linreg_fit
in utility.cpp
seem to work well enough, but a few things about logreg_fit
could be fleshed out more. In particular, could this function run faster if we used the L-BFGS algorithm? And, could we go one step further and use L-BFGS to run penalized regression? I don't know much about this area other than it appears there are libraries for it in C++ and they may work with armadillo.
@ciaran-evans, would you be interested in seeing if it would be feasible to write a logistic regression function using L-BFGS that runs faster than the one in aorsf
? The new function could just be a stand alone .cpp file at first and we could work through pulling it into aorsf
later. No pressure...this is a loosely defined problem, and it's perfectly alright if you would like to work on a different thing. One potential pro is that this is not time-sensitive.
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