What is the main difference between logistic regression and linear regression?
Practice Questions
1 question
Q1
What is the main difference between logistic regression and linear regression?
Logistic regression predicts continuous values, while linear regression predicts categorical values.
Logistic regression is used for classification, while linear regression is used for regression tasks.
Logistic regression requires more data than linear regression.
There is no difference; they are the same.
Logistic regression is used for binary classification tasks, while linear regression is used for predicting continuous values.
Questions & Step-by-step Solutions
1 item
Q
Q: What is the main difference between logistic regression and linear regression?
Solution: Logistic regression is used for binary classification tasks, while linear regression is used for predicting continuous values.
Steps: 3
Step 1: Understand that linear regression is used when we want to predict a number, like height or price.
Step 2: Know that logistic regression is used when we want to classify something into two categories, like yes/no or true/false.
Step 3: Remember that linear regression gives us a straight line as a result, while logistic regression gives us an S-shaped curve (sigmoid) to show probabilities.
