From 50c56914446198cc5fb2e4cdad183f198a0c5c19 Mon Sep 17 00:00:00 2001 From: "jeremie.desgagne.bouchard" Date: Wed, 4 Oct 2023 23:05:09 -0400 Subject: [PATCH] typos --- docs/src/index.md | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/docs/src/index.md b/docs/src/index.md index 28eee7ad..116c3c27 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -54,7 +54,7 @@ preds = m(x_train) ### Tables and DataFrames input -When using a Tables compatible input such as DataFrames, features with elements types `Real` (incl. `Bool`) and `Categorical` are automatically recognized as input features. Alternatively, `fnames` kwarg can be used. +When using a `Tables` compatible input such as `DataFrames`, features with element type `Real` (incl. `Bool`) and `Categorical` are automatically recognized as input features. Alternatively, `fnames` kwarg can be used. `Categorical` features are treated accordingly by the algorithm. Ordered variables will be treated as numerical features, using `≤` split rule, while unordered variables are using `==`. Support is currently limited to a maximum of 255 levels. `Bool` variables are treated as unordered, 2-levels cat variables. @@ -155,8 +155,7 @@ julia> x = recode(x_cat_m1, missing => "missing value") ### Target -Target variable must have its elements type `<:Real`. Only exception is for `EvoTreeClassifier` for which `CategoricalValue` and `String` are also supported. - +Target variable must have its element type `<:Real`. Only exception is for `EvoTreeClassifier` for which `CategoricalValue`, `Integer`, `String` and `Char` are supported. ## Save/Load