RStudio 2018 Conference Presentation and Materials

We've released our videos of the talks at the 2018 RStudio conference. My talk was Modeling in the Tidyverse (video) and I was also in the Tidyverse fireside chat (video). There are a lot of great talks on the conference website.

I also conducted a two day workshop on caret and the new modeling packages (recipes, rsample, tidyposterior and others) at the conference. The was no video of that, but all of the materials can be found in the course GitHub repository.

There will be at least one other workshop for this year on these topics. When that is finalized, I'll post the details here and on on twitter.

(the image above is from the workshop and is from tidyposterior)

Lots of Package News

I've sent a slew of packages to CRAN recently (thanks to Swetlana and Uwe). There are updates to:

• caret was primarily updated to deal with an issue introduced in the last version. It is a good idea to avoid fully loading the underlying modeling packages to avoid name conflicts. We made that change in the last version and it ended up being more complex than thought. A quirk in the regression tests missed it too but the whole thing can be avoided by loading the modeling package. news file

• rsample had some modest additions including bridges to caret and recipes. The website added more application examples (times series and survival analysis). news file

• recipes had more substantial enhancments including six new steps, a better interface for creating interactions (using selectors), and the ability to save the processed data in a sparse format. news file

• Cubist and C50 have been updated and brought into the age of roxygen and pkgdown. C5.0 now has a nice plot method a la partykit and now has a vignette. I'll be adding a few features to each over time.

Two new packages:

• yardstick contains many of the performance measurement methods in caret but in a format that is easier to use with dplyr syntax and functional programming.

• tidyposterior is a Bayesian version of caret's resamples function. It can be used to take the resampling results from multiple models and do more formal statistical comparisons. It is similar in spirit to Benavoli et al (2017). We are looking for nominations for the hex logo so please offer your suggestions (but keep it clean).