Use RulesClassifier to fix @load

docs/src/basic-example.jl

@@ -1,5 +1,5 @@
 ### A Pluto.jl notebook ###
-# v0.19.28
+# v0.19.29
 
 using Markdown
 using InteractiveUtils
@@ -91,16 +91,21 @@ Next, we can load the model that we want to use.
 Since Haberman's outcome column (`survival`) contains 0's and 1's, we use the `StableRulesClassifier`.
 We can make the `StableRulesClassifier` symbol available via MLJ's `@load`:
 ```julia
-StableRulesClassifier = @load StableRulesClassifier pkg="SIRUS"
+RulesClassifier = @load StableRulesClassifier pkg="SIRUS"
 ```
 or directly via
 ```julia
 using SIRUS: StableRulesClassifier
+RulesClassifier = StableRulesClassifier
 ```
 """
 
+# ╔═╡ 9a34a577-e69e-4c99-a564-46ab0672168b
+# Don't run this line if you used `@load StableRulesClassifier pkg="SIRUS"`.
+RulesClassifier = StableRulesClassifier;
+
 # ╔═╡ ccce5f3e-e396-4765-bf5f-6f79e905aca8
-model = StableRulesClassifier(; rng=StableRNG(1), q=4, max_depth=2, max_rules=8);
+model = RulesClassifier(; rng=StableRNG(1), q=4, max_depth=2, max_rules=8);
 
 # ╔═╡ 97c9ea2a-2897-472b-b15e-215f40049cf5
 md"""
@@ -195,6 +200,7 @@ evaluate(model, X, y; resampling, measure=auc)
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