In a regression problem, what does the R-squared value indicate?
Practice Questions
1 question
Q1
In a regression problem, what does the R-squared value indicate?
The strength of the relationship between variables
The number of features used in the model
The accuracy of the classification
The error rate of the predictions
R-squared indicates the strength of the relationship between the independent variables and the dependent variable in regression.
Questions & Step-by-step Solutions
1 item
Q
Q: In a regression problem, what does the R-squared value indicate?
Solution: R-squared indicates the strength of the relationship between the independent variables and the dependent variable in regression.
Steps: 4
Step 1: Understand that in a regression problem, we are trying to predict a dependent variable (the outcome) using one or more independent variables (the predictors).
Step 2: R-squared is a statistical measure that tells us how well the independent variables explain the variation in the dependent variable.
Step 3: R-squared values range from 0 to 1. A value of 0 means that the independent variables do not explain any of the variation in the dependent variable, while a value of 1 means they explain all the variation.
Step 4: A higher R-squared value indicates a stronger relationship between the independent variables and the dependent variable, meaning the model is better at predicting the outcome.
