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ropensci / aorsf

Accelerated Oblique Random Survival Forests
https://docs.ropensci.org/aorsf
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utility functions for logistic regression and ols #23

Open bcjaeger opened 11 months ago

bcjaeger commented 11 months ago

default methods to find linear combos of predictors in classification and regression trees

bcjaeger commented 10 months ago

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.