From 3a31a6da705fb31a3911c0ba9ff418ace3409c64 Mon Sep 17 00:00:00 2001 From: James Melville Date: Tue, 12 Dec 2023 07:33:32 -0800 Subject: [PATCH] Fix some links --- vignettes/articles/nearest-neighbors-format.Rmd | 2 +- vignettes/uwot.Rmd | 6 ++---- 2 files changed, 3 insertions(+), 5 deletions(-) diff --git a/vignettes/articles/nearest-neighbors-format.Rmd b/vignettes/articles/nearest-neighbors-format.Rmd index 19a94666..3b085bcc 100644 --- a/vignettes/articles/nearest-neighbors-format.Rmd +++ b/vignettes/articles/nearest-neighbors-format.Rmd @@ -145,7 +145,7 @@ you passed in, and the list item names will be `precomputed`. ## Multiple neighbor data As discussed under the -[Mixed Data Types](https://github.com/jlmelville/uwot#mixed-data-types) section, +[Mixed Data Types](https://jlmelville.github.io/uwot/articles/mixed-data-types.html) article, you can apply multiple distance metrics to different parts of matrix or data frame input data. if you do this, then `ret_nn` will return all the neighbor data. The list under `nn` will now contain as many items as metrics, diff --git a/vignettes/uwot.Rmd b/vignettes/uwot.Rmd index 67ac4c08..1c19e7d6 100644 --- a/vignettes/uwot.Rmd +++ b/vignettes/uwot.Rmd @@ -289,9 +289,7 @@ cosine distance applied to row-centered vectors. If you need other metrics, and can generate the nearest neighbor info externally, you can pass the data directly to `uwot` via the `nn_method` -parameter. See the -[Nearest Neighbor Data Format section](https://github.com/jlmelville/uwot#nearest-neighbor-data-format) -for more details. Please note that the Hamming support is a lot slower than the +parameter. Please note that the Hamming support is a lot slower than the other metrics. I do not recommend using it if you have more than a few hundred features, and even then expect it to take several minutes during the index building phase in situations where the Euclidean metric would take only a few @@ -345,7 +343,7 @@ measurements, and no support for sparse matrix data input. However, `uwot` *does* let you pass in nearest neighbor data. So if you have access to other nearest neighbor methods, you can generate data that can be used with `uwot`. See the -[Nearest Neighbor Data Format](https://github.com/jlmelville/uwot#nearest-neighbor-data-format) +[Nearest Neighbor Data Format](https://jlmelville.github.io/uwot/articles/nearest-neighbors-format.html) article. Or if you can calculate a distance matrix for your data, you can pass it in as `dist` object.