From 58d90bc65e95a11718e63a0834809d156dcf431d Mon Sep 17 00:00:00 2001 From: Saeed Esmaili Date: Tue, 12 Sep 2023 12:14:12 +0200 Subject: [PATCH] Add new line to fix markdown bullet point formatting (#1519) --- docs/getting_started/outlier_reduction/outlier_reduction.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/getting_started/outlier_reduction/outlier_reduction.md b/docs/getting_started/outlier_reduction/outlier_reduction.md index 8033ce7b..fbb05d23 100644 --- a/docs/getting_started/outlier_reduction/outlier_reduction.md +++ b/docs/getting_started/outlier_reduction/outlier_reduction.md @@ -27,7 +27,8 @@ new_topics = topic_model.reduce_outliers(docs, topics) The default method for reducing outliers is by calculating the c-TF-IDF representations of outlier documents and assigning them to the best matching c-TF-IDF representations of non-outlier topics. -However, there are a number of other strategies one can use, either seperately or in conjunction that are worthwhile to explore: +However, there are a number of other strategies one can use, either separately or in conjunction that are worthwhile to explore: + * Using the topic-document probabilities to assign topics * Using the topic-document distributions to assign topics * Using c-TF-IDF representations to assign topics