From f1f7dfe207a07521d357cb85234fcd3266a2d975 Mon Sep 17 00:00:00 2001 From: Essam Date: Sat, 31 Aug 2024 21:23:36 -0500 Subject: [PATCH] =?UTF-8?q?=E2=9C=85=20Improve=20docstring?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/types.jl | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/src/types.jl b/src/types.jl index fc9a4ce..f0edd14 100644 --- a/src/types.jl +++ b/src/types.jl @@ -200,10 +200,11 @@ as described in Entity Embeddings of Categorical Variables by Cheng Guo, Felix B const XDOC = """ - `X` is either a `Matrix` or any table of input features (eg, a `DataFrame`) whose columns are of scitype - `Multiclass` or `OrderedFactor`; check column scitypes with `schema(X)`. - If `X` is a `Matrix`, it is assumed to have columns corresponding to features and rows + `Continuous` or `Multiclass` or `OrderedFactor`; check column scitypes with `schema(X)`. + If `X` is a `Matrix`, it is assumed to be purely continuous and to have columns corresponding to features and rows corresponding to observations. - In case any `Multiclass` or `OrderedFactor` columns appear in `X`, the constructed network will use an `EntityEmbedder` layer to transform them into dense vectors. + In case any `Multiclass` or `OrderedFactor` columns appear in `X`, the constructed network will use an `EntityEmbedder` layer + to transform them into dense vectors. """ const EMBDOC = """