autoxgboost
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ja-thomas
autoxgboost - Automatic tuning and fitting of xgboost
would you consider this an interesting glass box algo for use? good accuracy and interpretability sounds interesting https://cran.r-project.org/web/packages/interpret/index.html
Unable to install. Repeated failures with: ``` Error : (converted from warning) package 'ParamHelpers' was built under R version 3.5.3 ERROR: lazy loading failed for package 'autoxgboost' ```
I've run your example code: ```{r} iris.task = makeClassifTask(data = iris, target = "Species") ctrl = makeMBOControl() ctrl = setMBOControlTermination(ctrl, iters = 1L) #Speed up Tuning by only doing 1...
Hi How can i get the feature importance from the final model output from autoxgboost? system.time(tuned.labeled.autoxgboost
I left a note here: #35, but thought it might warrant its own issue (if this package is still being developed). `scale_pos_weight` is only for binary classification, is there an...
xgboost has included a new target function for cox regression (`survival:cox`). Will it be possible to extend the package to also support the auto tuning of survival models?
I made a benchmark comparing it with `ranger` and `tuneRanger` in the default mode on some regression datasets (surprisingly `tuneRanger` was quite good, maybe datasets too small?) and noticed, that...
I'm not familiar with the statistical approach taken by mlrMBO, so excuse me if I'm missing something. Anyway, I was going to ask a question about overfitting in autoxgboost, but...
Hello, Thanks for making autoxgboost, seems like a great effort. I wanted to report an error I just received while testing it out: ```r Error in chol.default(R) : the leading...
https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxhdXRvbWwyMDE4aWNtbHxneDo3M2ViMmRkNDU4OGYxZjhh and H2O autoML
