diff --git a/NEWS.md b/NEWS.md
index a93afede..54ae70f9 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -27,6 +27,10 @@ in the documentation, and also the rnndescent package's
 [documentation](https://jlmelville.github.io/rnndescent/index.html) for details.
 `rnndescent` is only a suggested package, not a requirement, so you need to 
 install it yourself (e.g. via `install.packages("rnndescent")`).
+* New function: `umap2`, which acts like `umap` but with modified defaults,
+reflecting my experience with UMAP and correcting some small mistakes. See the
+[umap2 article](https://jlmelville.github.io/uwot/articles/umap2.html) for more
+details.
 
 ## Bug fixes and minor improvements
 
diff --git a/R/umap2.R b/R/umap2.R
index 2935eb45..0b9e6a58 100644
--- a/R/umap2.R
+++ b/R/umap2.R
@@ -593,9 +593,6 @@
 #' @examples
 #'
 #' iris30 <- iris[c(1:10, 51:60, 101:110), ]
-#'
-#' # Non-numeric columns are automatically removed so you can pass data frames
-#' # directly in a lot of cases without pre-processing
 #' iris_umap <- umap2(iris30, n_neighbors = 5)
 #'
 #' @references
diff --git a/README.md b/README.md
index 5fb65538..02230ecf 100644
--- a/README.md
+++ b/README.md
@@ -60,6 +60,11 @@ devtools::install_github("jlmelville/uwot")
 ```R
 library(uwot)
 
+# umap2 is a version of the umap() function with better defaults
+iris_umap <- umap2(iris)
+
+# but you can still use the umap function (which most of the existing 
+# documentation does)
 iris_umap <- umap(iris)
 
 # Load mnist from somewhere, e.g.
diff --git a/man/umap2.Rd b/man/umap2.Rd
index 854ecb49..648dd6db 100644
--- a/man/umap2.Rd
+++ b/man/umap2.Rd
@@ -43,7 +43,7 @@ umap2(
   grain_size = 1,
   tmpdir = tempdir(),
   verbose = getOption("verbose", TRUE),
-  batch = FALSE,
+  batch = TRUE,
   opt_args = NULL,
   epoch_callback = NULL,
   pca_method = NULL,
@@ -697,9 +697,6 @@ compatibility. In addition:
 \examples{
 
 iris30 <- iris[c(1:10, 51:60, 101:110), ]
-
-# Non-numeric columns are automatically removed so you can pass data frames
-# directly in a lot of cases without pre-processing
 iris_umap <- umap2(iris30, n_neighbors = 5)
 
 }