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Merged
ablaom merged 2 commits into from
Aug 28, 2026
Merged

Evo trees update #66

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1f6243d
adapt to bug fix at EvoTrees after bumping compat for that pkg
ablaom Aug 28, 2026
604f963
update readme
ablaom Aug 28, 2026
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3 changes: 1 addition & 2 deletions README.md
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Expand Up @@ -72,5 +72,4 @@ using NotebookManagementTools
generate(joinpath("docs", "src", "notebooks", "02_models"))
```

but change "02_models" to the tutorial you are testing. If you are adding a brand new
tutorial, *do commit* the generated markdown, but for updates this is discouraged.
but change "02_models" to the tutorial you are testing.
2 changes: 1 addition & 1 deletion docs/src/notebooks/MLJTutorial/03_pipelines/Project.toml
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Expand Up @@ -10,7 +10,7 @@ MLJMultivariateStatsInterface = "1b6a4a23-ba22-4f51-9698-8599985d3728"
[compat]
CSV = "0.10.16"
DataFrames = "1.8.2"
EvoTrees = "0.18"
EvoTrees = "0.19"
MLJ = "0.23.3"
MLJLinearModels = "0.10.2"
MLJMultivariateStatsInterface = "0.5.4"
2 changes: 1 addition & 1 deletion docs/src/notebooks/MLJTutorial/04_tuning/Project.toml
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Expand Up @@ -12,7 +12,7 @@ Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
CSV = "0.10.16"
DataFrames = "1.8.2"
Distributions = "0.25.130"
EvoTrees = "0.18"
EvoTrees = "0.19"
MLJ = "0.23.3"
MLJLinearModels = "0.10.2"
Plots = "1.41.6"
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6 changes: 4 additions & 2 deletions docs/src/notebooks/MLJTutorial/04_tuning/notebook.jl
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Expand Up @@ -237,11 +237,13 @@ tree_booster = EvoTreeRegressor(nrounds = 70)
model = ContinuousEncoder |> tree_booster

# (a) Construct a bounded range `r1` for the `evo_tree_booster`
# parameter `max_depth`, varying between 1 and 12.
# parameter `max_depth`, varying between 4 and 14.

# (b) For the `colsample` parameter of the `EvoTreeRegressor`, define the range

r2 = range(model, :(evo_tree_regressor.colsample), lower=0.5, upper=1.0)
r2 = range(model, :(evo_tree_regressor.nbins), values = [32, 64, 128])

# (a)

# Optimize `model` over these the parameter ranges `r1` and `r2` using a random search
# with uniform priors (the default). Use `Holdout()` resampling, and implement your search
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2 changes: 1 addition & 1 deletion docs/src/notebooks/MLJTutorial/99_solution_to_exercises/Project.toml
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Expand Up @@ -17,7 +17,7 @@ CSV = "0.10.16"
DataFrames = "1.8.2"
Distributions = "0.25.130"
Downloads = "1.7.0"
EvoTrees = "0.18"
EvoTrees = "0.19"
MLJ = "0.23.3"
MLJClusteringInterface = "0.1.13"
MLJDecisionTreeInterface = "0.5.0"
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6 changes: 3 additions & 3 deletions docs/src/notebooks/MLJTutorial/99_solution_to_exercises/notebook.jl
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@@ -1,4 +1,4 @@
# # Solutions to Exercises
# # Solutions to Exercises

using MLJ, Downloads, CSV, DataFrames, Plots
nothing #hide
Expand Down Expand Up @@ -330,11 +330,11 @@ EvoTreeRegressor = @load EvoTreeRegressor
tree_booster = EvoTreeRegressor(nrounds = 70)
model = ContinuousEncoder |> tree_booster

r2 = range(model, :(evo_tree_regressor.colsample), lower=0.5, upper=1.0)
r2 = range(model, :(evo_tree_regressor.nbins), values = [32, 64, 128])

# (a)

r1 = range(model, :(evo_tree_regressor.max_depth), lower=1, upper=12)
r1 = range(model, :(evo_tree_regressor.max_depth), lower=4, upper=14)

# (b)

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