Ace the Azure AI-900 exam! Understand R-squared scores, their interpretation in regression models, and identify the best value for optimal model performance.
Table of Contents
Question
Which of the following is the best R-squared score?
A. 0.8
B. 0.57
C. 0.18
D. 1.2
Answer
A. 0.8
Explanation
R-squared, also known as the coefficient of determination, is a statistical measure in regression models that indicates the proportion of variance in the dependent variable that can be explained by the independent variable(s) [3, 6, 8, 10, 19]. It essentially measures how well a model fits the data.
Here’s a breakdown of R-squared and why 0.8 is the best choice among the options:
Range
R-squared values range from 0 to 1 [3, 8]. A score of 1 indicates a perfect fit where the model explains all the variability in the dependent variable, while 0 indicates the model explains none of the variability [2, 3, 6].
Interpretation
A higher R-squared value generally indicates a better fit, meaning the model explains more of the variance in the target variable15. For example, an R-squared of 0.8 (or 80%) means that 80% of the variability in the dependent variable is explained by the model [6, 15].
Why 0.8 is best
Among the given options, 0.8 is the highest value within the valid range (0 to 1) for R-squared [3, 8]. Therefore, it represents the model that explains the most variance in the dependent variable [6, 15].
Why other options are incorrect
B. 0.57 and C. 0.18 are valid R-squared values, but they indicate a weaker fit than 0.8 [6, 15].
D. 1.2 is not a valid R-squared value as it exceeds the maximum possible value of 1 [3, 8].
While a high R-squared is generally desirable, it’s important to consider the context of the problem and other evaluation metrics [2, 6, 15]. A low R-squared doesn’t automatically mean the model is bad, especially when looking for weak signals, and a high R-squared doesn’t guarantee the model is unbiased or makes accurate predictions [6, 12, 15].
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.