From dfae7ff50319dbe18a2c09263325f5e51e6c04f3 Mon Sep 17 00:00:00 2001 From: "opensearch-trigger-bot[bot]" <98922864+opensearch-trigger-bot[bot]@users.noreply.github.com> Date: Mon, 13 Nov 2023 12:52:11 -0500 Subject: [PATCH] Link fix (#5568) (#5569) (#5575) (cherry picked from commit e4f058017236e330db4289f3b853b87171c0dcc4) (cherry picked from commit 3daf72e046e51e057f0687ea29e51cd1370c918c) Signed-off-by: Fanit Kolchina Signed-off-by: github-actions[bot] Co-authored-by: github-actions[bot] --- _ml-commons-plugin/algorithms.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/_ml-commons-plugin/algorithms.md b/_ml-commons-plugin/algorithms.md index 7fccd92d8b..6a4d21531b 100644 --- a/_ml-commons-plugin/algorithms.md +++ b/_ml-commons-plugin/algorithms.md @@ -434,11 +434,11 @@ A classification algorithm, logistic regression models the probability of a disc ### Example: Train/Predict with Iris data -The following example creates an index in OpenSearch with the [Iris dataset](https://archive.ics.uci.edu/ml/datasets/iris), then trains the data using logistic regression. Lastly, it uses the trained model to predict Iris types separated by row. +The following example creates an index in OpenSearch with the [Iris dataset](https://en.wikipedia.org/wiki/Iris_flower_data_set), then trains the data using logistic regression. Lastly, it uses the trained model to predict Iris types separated by row. #### Create an Iris index -Before using this request, make sure that you have downloaded [Iris data](https://archive.ics.uci.edu/ml/datasets/iris). +Before using this request, make sure that you have downloaded [Iris data](https://archive.ics.uci.edu/dataset/53/iris). ```bash PUT /iris_data