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Question 44 - H13-311_V3.5 discussion

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The mean squared error (MSE) loss function cannot be used for classification problems.

A.
TRUE
Answers
A.
TRUE
B.
FALSE
Answers
B.
FALSE
Suggested answer: A

Explanation:

The mean squared error (MSE) loss function is primarily used for regression problems, where the goal is to minimize the difference between the predicted and actual continuous values. For classification problems, where the target output is categorical (e.g., binary or multi-class labels), loss functions like cross-entropy are more suitable, as they are designed to handle the probabilistic interpretation of outputs in classification tasks.

Using MSE for classification could lead to inefficient training because it doesn't capture the probabilistic relationships required for classification tasks.

asked 26/09/2024
Christoph Reithmayr
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