From a846132275e5deaa0a248d0e4a6b9c48268a7159 Mon Sep 17 00:00:00 2001 From: Vidushi Gupta <55969597+Vidushi-Gupta@users.noreply.github.com> Date: Mon, 3 Jul 2023 17:48:40 +0530 Subject: [PATCH] Changed orange to white in binary classification --- 2-Regression/4-Logistic/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/2-Regression/4-Logistic/README.md b/2-Regression/4-Logistic/README.md index 321de9d59..6d3c2d1e3 100644 --- a/2-Regression/4-Logistic/README.md +++ b/2-Regression/4-Logistic/README.md @@ -41,7 +41,7 @@ Logistic regression differs from linear regression, which you learned about prev ### Binary classification -Logistic regression does not offer the same features as linear regression. The former offers a prediction about a binary category ("orange or not orange") whereas the latter is capable of predicting continual values, for example given the origin of a pumpkin and the time of harvest, _how much its price will rise_. +Logistic regression does not offer the same features as linear regression. The former offers a prediction about a binary category ("white or not white") whereas the latter is capable of predicting continual values, for example given the origin of a pumpkin and the time of harvest, _how much its price will rise_. ![Pumpkin classification Model](./images/pumpkin-classifier.png) > Infographic by [Dasani Madipalli](https://twitter.com/dasani_decoded)