Treating a categorical variable as a continuous variable can sometimes lead to better predictive models, but it depends on the nature of the variable and the specific problem at hand. Which of the following statements best captures this idea?
A) Yes, treating categorical variables as continuous can improve model performance by capturing more nuanced relationships.
B) No, treating categorical variables as continuous can introduce noise and distort the interpretation of the variable's effect on the outcome.
C) It depends on the algorithm used; some algorithms perform better with categorical variables treated as continuous, while others do not.
D) Treating categorical variables as continuous is always preferable to maintain consistency in modeling approaches.
