From d22b293f2f26ce10e8100d07b4053a2fc8656704 Mon Sep 17 00:00:00 2001 From: Jeff H Date: Wed, 7 Jul 2021 00:15:07 -0500 Subject: [PATCH] Update reference to treelite website (#7084) treelite.io is no longer a valid site and re-directs users to a parked domain. Re-directing to the documentation is safer at this point. --- doc/tutorials/model.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/tutorials/model.rst b/doc/tutorials/model.rst index a3c0dfb37..701fc9943 100644 --- a/doc/tutorials/model.rst +++ b/doc/tutorials/model.rst @@ -105,7 +105,7 @@ where :math:`K` is the number of trees, :math:`f` is a function in the functiona Now here comes a trick question: what is the *model* used in random forests? Tree ensembles! So random forests and boosted trees are really the same models; the difference arises from how we train them. This means that, if you write a predictive service for tree ensembles, you only need to write one and it should work -for both random forests and gradient boosted trees. (See `Treelite `_ for an actual example.) One example of why elements of supervised learning rock. +for both random forests and gradient boosted trees. (See `Treelite `_ for an actual example.) One example of why elements of supervised learning rock. ************* Tree Boosting