Question 1

+2−0Multiple correct

Which of the following statements accurately describes the key difference between classification and regression models?

Select all that apply.

A.
In classification, the output variable is continuous and real-valued, while in regression, it is categorical.
B.
Regression models are used for predicting probabilities, whereas classification models focus on predicting absolute values.
C.
Classification models aim to find decision boundaries to separate data into classes, while regression models seek to predict a numeric value.
D.
In regression, the commonly used loss function is mean squared error, while in classification, 0 -1 loss is typically employed.

+2−0Multiple correct

Which of the following statements accurately describes the key difference between classification and regression models?

Select all that apply.

A.
In classification, the output variable is continuous and real-valued, while in regression, it is categorical.
B.
Regression models are used for predicting probabilities, whereas classification models focus on predicting absolute values.
C.
Classification models aim to find decision boundaries to separate data into classes, while regression models seek to predict a numeric value.
D.
In regression, the commonly used loss function is mean squared error, while in classification, 0 -1 loss is typically employed.

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