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Hannah Frick

aorsf - accelerated oblique random survival forest

Thank you for the great PR! 🙌

Add `aorsf` engine to rand_forest?

closed in #211

Using `fit_resamples` with `set_mode("censored regression")` produces `Error in check_metrics(): ! Unknown mode for parsnip model`

We are actively working on adding metrics for censored regression to yardstick, anything related to tuning is on the list next!

Using `fit_resamples` with `set_mode("censored regression")` produces `Error in check_metrics(): ! Unknown mode for parsnip model`

All good, it's nice to know that it will be used!

Using `fit_resamples` with `set_mode("censored regression")` produces `Error in check_metrics(): ! Unknown mode for parsnip model`

Things are coming together! We have improved how workflows with censored regression models are handled, we have performance metrics for these models, and we can tune them. This is currently...

Using `fit_resamples` with `set_mode("censored regression")` produces `Error in check_metrics(): ! Unknown mode for parsnip model`

Forgot to close this when I posted the update on the dev versions ⚡

Enable data-related args to `survival::coxph()`

Also https://github.com/tidymodels/stacks/pull/117 for dealing with parsnip's quosures since https://github.com/tidymodels/parsnip/pull/737 put an end to https://github.com/tidymodels/parsnip/issues/713 mentioned above

multi-predict for some prediction types

possible todo: `mboost`

multi-predict for some prediction types

Added the remaining prediction types of glmnet models in #282 , and am going to close this issue in favor of a new one specifically for mboost: #290

Add `randomForestSRC` engine to `rand_forest()`

Yes, they are! (PRs welcome 😊 )