vignette and blog links

README.org

@@ -17,6 +17,8 @@ framework in R
 
 *** Algorithm 1: cross-validation for comparing train on same and other
 
+See examples in [[https://cloud.r-project.org/web/packages/mlr3resampling/vignettes/ResamplingSameOtherCV.html][vignette]] and data viz for [[https://tdhock.github.io/2023-12-13-train-predict-subsets-regression/][regression]] and [[https://tdhock.github.io/2023-12-13-train-predict-subsets-classification/][classification]].
+
 A supervised learning algorithm inputs a train set, and outputs a
 prediction function, which can be used on a test set. If each data
 point belongs to a group (such as geographic region, year, etc), then
@@ -45,6 +47,8 @@ List of 1
 
 *** Algorithm 2: cross-validation for comparing different sized train sets
 
+See examples in [[https://cloud.r-project.org/web/packages/mlr3resampling/vignettes/ResamplingVariableSizeTrainCV.html][vignette]] and data viz for [[https://tdhock.github.io/2023-12-26-train-sizes-regression/][regression]] and [[https://tdhock.github.io/2023-12-27-train-sizes-classification/][classification]].
+
 How many train samples are required to get accurate predictions on a
 test set? Cross-validation can be used to answer this question, with
 variable size train sets. This is implemented in
@@ -62,11 +66,15 @@ List of 4
  $ train_sizes   : int 5
 #+end_src
 
-*** More Usage Examples
+*** More Usage Examples and Discussion
+
+The examples linked below have examples with larger data sizes than
+the examples in the CRAN vignettes linked above.
 
-See https://tdhock.github.io/blog/2023/R-gen-new-subsets/ and [[https://cloud.r-project.org/web/packages/mlr3resampling/][vignettes on CRAN]].
+* https://tdhock.github.io/blog/2023/R-gen-new-subsets/
+* [[https://tdhock.github.io/blog/2023/variable-size-train/]]
 
-*** Related work
+** Related work
 
 mlr3resampling code was copied/modified from Resampling and
 ResamplingCV classes in the excellent [[https://github.com/mlr-org/mlr3][mlr3]] package.