Answer-first summary for fast verification
Answer: No
The solution does NOT meet the goal because it includes classification metrics (Accuracy, Precision, Recall, F1 score, and AUC) which are inappropriate for evaluating a linear regression model. Linear regression is used for continuous value prediction, not classification. While Relative Squared Error and Coefficient of Determination (R²) are valid regression metrics, the inclusion of classification metrics makes the overall solution incorrect. The community discussion confirms that R² and RSE are appropriate for regression, but the presence of classification metrics invalidates the solution.
Author: LeetQuiz Editorial Team
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You are creating a model to predict the price of a student's artwork based on the student's length of education, degree type, and art form. You start by creating a linear regression model. You need to evaluate the linear regression model.
Solution: Use the following metrics: Relative Squared Error, Coefficient of Determination, Accuracy, Precision, Recall, F1 score, and AUC.
Does the solution meet the goal?
A
Yes
B
No
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