From 0bcfd5d615abac7e12bc2d8b4a41951ad3e2fcf4 Mon Sep 17 00:00:00 2001 From: Vidushi Gupta <55969597+Vidushi-Gupta@users.noreply.github.com> Date: Mon, 3 Jul 2023 16:48:39 +0530 Subject: [PATCH] Updated infographics Changed the logistic regression and the multinomial v/s ordinal regression infographics --- 2-Regression/4-Logistic/solution/R/lesson_4.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/2-Regression/4-Logistic/solution/R/lesson_4.Rmd b/2-Regression/4-Logistic/solution/R/lesson_4.Rmd index 6bf95bf017..8bda949910 100644 --- a/2-Regression/4-Logistic/solution/R/lesson_4.Rmd +++ b/2-Regression/4-Logistic/solution/R/lesson_4.Rmd @@ -12,7 +12,7 @@ output: ## Build a logistic regression model - Lesson 4 -![Infographic by Dasani Madipalli](../../images/logistic-linear.png){width="600"} +![Logistic vs. linear regression infographic](https://github.com/microsoft/ML-For-Beginners/blob/main/2-Regression/4-Logistic/images/linear-vs-logistic.png) #### **[Pre-lecture quiz](https://gray-sand-07a10f403.1.azurestaticapps.net/quiz/15/)** @@ -80,7 +80,7 @@ There are other types of logistic regression, including multinomial and ordinal: - **Ordinal**, which involves ordered categories, useful if we wanted to order our outcomes logically, like our pumpkins that are ordered by a finite number of sizes (mini,sm,med,lg,xl,xxl). -![Infographic by Dasani Madipalli](../../images/multinomial-ordinal.png){width="600"} +![Multinomial vs ordinal regression](https://github.com/microsoft/ML-For-Beginners/blob/main/2-Regression/4-Logistic/images/multinomial-vs-ordinal.png) \ **It's still linear**