Answer-first summary for fast verification
Answer: No
The proposed solution includes both regression metrics (Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error) and classification metrics (Accuracy, Precision, Recall, F1 score, AUC). Linear regression is used for predicting continuous numerical values (like artwork prices), not for classification tasks. Therefore, classification metrics are inappropriate for evaluating a linear regression model. As confirmed in the community discussion and the answer description, classification metrics should not be used for regression models. The solution does not meet the goal because it includes metrics that are not applicable to linear regression.
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 begin by creating a linear regression model.
You need to evaluate the linear regression model.
Proposed Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error, Accuracy, Precision, Recall, F1 score, and AUC.
Does the proposed solution meet the goal?
A
Yes
B
No
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