From a91374cdb49113e8c3c9bb005b4a727fb3557fb2 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Thu, 3 Aug 2023 11:15:06 +0200
Subject: [PATCH] CompatHelper: bump compat for EvoTrees to 0.15 for package
 test, (keep existing compat) (#91)

* CompatHelper: bump compat for EvoTrees to 0.15 for package test, (keep existing compat)

* Adjust some hyperparameters

---------

Co-authored-by: CompatHelper Julia <compathelper_noreply@julialang.org>
Co-authored-by: David Widmann <devmotion@users.noreply.github.com>
---
 test/Project.toml | 2 +-
 test/rstar.jl     | 8 ++++----
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/test/Project.toml b/test/Project.toml
index 980db347..e1909c9c 100644
--- a/test/Project.toml
+++ b/test/Project.toml
@@ -21,7 +21,7 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 [compat]
 Distributions = "0.25"
 DynamicHMC = "3"
-EvoTrees = "0.14.7"
+EvoTrees = "0.14.7, 0.15"
 FFTW = "1.1"
 LogDensityProblems = "0.12, 1, 2"
 LogExpFunctions = "0.3"
diff --git a/test/rstar.jl b/test/rstar.jl
index cd445789..848fb221 100644
--- a/test/rstar.jl
+++ b/test/rstar.jl
@@ -25,8 +25,8 @@ end
     @testset "samples input type: $wrapper" for wrapper in [Vector, Array, Tables.table]
         # In practice, probably you want to use EvoTreeClassifier with early stopping
         classifiers = (
-            EvoTreeClassifier(; nrounds=100, eta=0.3),
-            Pipeline(EvoTreeClassifier(; nrounds=100, eta=0.3); operation=predict_mode),
+            EvoTreeClassifier(; nrounds=1_000, eta=0.1),
+            Pipeline(EvoTreeClassifier(; nrounds=1_000, eta=0.1); operation=predict_mode),
             DecisionTreeClassifier(),
             SVC(),
             XGBoostClassifiers...,
@@ -128,9 +128,9 @@ end
         # In practice, probably you want to use EvoTreeClassifier with early stopping
         rng = MersenneTwister(42)
         classifiers = (
-            EvoTreeClassifier(; rng=rng, nrounds=100, eta=0.3),
+            EvoTreeClassifier(; rng=rng, nrounds=1_000, eta=0.1),
             Pipeline(
-                EvoTreeClassifier(; rng=rng, nrounds=100, eta=0.3); operation=predict_mode
+                EvoTreeClassifier(; rng=rng, nrounds=1_000, eta=0.1); operation=predict_mode
             ),
             DecisionTreeClassifier(; rng=rng),
             SVC(),