diff --git a/Project.toml b/Project.toml index 5065b1c..b28671f 100644 --- a/Project.toml +++ b/Project.toml @@ -1,7 +1,7 @@ name = "MLJDecisionTreeInterface" uuid = "c6f25543-311c-4c74-83dc-3ea6d1015661" authors = ["Anthony D. Blaom "] -version = "0.2.5" +version = "0.3.0" [deps] DecisionTree = "7806a523-6efd-50cb-b5f6-3fa6f1930dbb" @@ -10,7 +10,7 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c" [compat] -DecisionTree = "0.11" +DecisionTree = "0.12" MLJModelInterface = "1.5" Tables = "1.6" julia = "1.6" diff --git a/src/MLJDecisionTreeInterface.jl b/src/MLJDecisionTreeInterface.jl index 281b58d..265878e 100644 --- a/src/MLJDecisionTreeInterface.jl +++ b/src/MLJDecisionTreeInterface.jl @@ -446,8 +446,7 @@ Train the machine using `fit!(mach, rows=...)`. - `min_purity_increase=0`: min purity needed for a split -- `n_subfeatures=0`: number of features to select at random (0 for all, - -1 for square root of number of features) +- `n_subfeatures=0`: number of features to select at random (0 for all) - `post_prune=false`: set to `true` for post-fit pruning @@ -772,8 +771,7 @@ Train the machine with `fit!(mach, rows=...)`. - `min_purity_increase=0`: min purity needed for a split -- `n_subfeatures=0`: number of features to select at random (0 for all, - -1 for square root of number of features) +- `n_subfeatures=0`: number of features to select at random (0 for all) - `post_prune=false`: set to `true` for post-fit pruning