From 86f0fb6fa5339099cf0b4ba5297a80795ad3e4ca Mon Sep 17 00:00:00 2001 From: deepyaman Date: Thu, 21 Mar 2024 15:05:52 +0000 Subject: [PATCH] deploy: fa422bdbb9524ca9b84d09e008abf7871ac22d41 --- reference/steps-encoding.html | 4 ++-- search.json | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/reference/steps-encoding.html b/reference/steps-encoding.html index 1b4dfcd..fc10c51 100644 --- a/reference/steps-encoding.html +++ b/reference/steps-encoding.html @@ -352,7 +352,7 @@

Parameters

Examples

>>> import ibisml as ml
-

One-hot encode all string columns

+

One-hot encode all string columns.

>>> step = ml.OneHotEncode(ml.string())

One-hot encode a specific column, only including categories with at least 20 samples.

>>> step = ml.OneHotEncode("x", min_frequency=20)
@@ -406,7 +406,7 @@

Parameters

Examples

>>> import ibisml as ml
-

Categorical encode all string columns

+

Categorical encode all string columns.

>>> step = ml.CategoricalEncode(ml.string())

Categorical encode a specific column, only including categories with at least 20 samples.

>>> step = ml.CategoricalEncode("x", min_frequency=20)
diff --git a/search.json b/search.json index 1722e87..008076d 100644 --- a/search.json +++ b/search.json @@ -292,7 +292,7 @@ "href": "reference/steps-encoding.html#examples", "title": "Encoding", "section": "Examples", - "text": "Examples\n>>> import ibisml as ml\nOne-hot encode all string columns\n>>> step = ml.OneHotEncode(ml.string())\nOne-hot encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.OneHotEncode(\"x\", min_frequency=20)\nOne-hot encode a specific column, including at most 10 categories.\n>>> step = ml.OneHotEncode(\"x\", max_categories=10)", + "text": "Examples\n>>> import ibisml as ml\nOne-hot encode all string columns.\n>>> step = ml.OneHotEncode(ml.string())\nOne-hot encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.OneHotEncode(\"x\", min_frequency=20)\nOne-hot encode a specific column, including at most 10 categories.\n>>> step = ml.OneHotEncode(\"x\", max_categories=10)", "crumbs": [ "Steps", "Encoding" @@ -314,7 +314,7 @@ "href": "reference/steps-encoding.html#examples-1", "title": "Encoding", "section": "Examples", - "text": "Examples\n>>> import ibisml as ml\nCategorical encode all string columns\n>>> step = ml.CategoricalEncode(ml.string())\nCategorical encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.CategoricalEncode(\"x\", min_frequency=20)\nCategorical encode a specific column, including at most 10 categories.\n>>> step = ml.CategoricalEncode(\"x\", max_categories=10)", + "text": "Examples\n>>> import ibisml as ml\nCategorical encode all string columns.\n>>> step = ml.CategoricalEncode(ml.string())\nCategorical encode a specific column, only including categories with at least 20 samples.\n>>> step = ml.CategoricalEncode(\"x\", min_frequency=20)\nCategorical encode a specific column, including at most 10 categories.\n>>> step = ml.CategoricalEncode(\"x\", max_categories=10)", "crumbs": [ "Steps", "Encoding"