explicitly referred to themis as an R package

Author: ttimbers

classification1.Rmd

@@ -1184,7 +1184,7 @@ fairly nuanced, and a careful treatment would require a lot more detail and math
 For the present purposes, it will suffice to rebalance the data by *oversampling* the rare class. \index{oversampling}
 In other words, we will replicate rare observations multiple times in our data set to give them more
 voting power in the $K$-nearest neighbor algorithm. In order to do this, we will add an oversampling
-step to the earlier `uc_recipe` recipe with the `step_upsample` function from the `themis` package. \index{recipe!step\_upsample}
+step to the earlier `uc_recipe` recipe with the `step_upsample` function from the `themis` R package. \index{recipe!step\_upsample}
 We show below how to do this, and also
 use the `group_by` and `summarize` functions to see that our classes are now balanced: