DP-100 Question #72: Real Exam Question with Answer & Explanation

Question

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are creating a new experiment in Azure Machine Learning Studio. One class has a much smaller number of observations than the other classes in the training set. You need to select an appropriate data sampling strategy to compensate for the class imbalance. Solution: You use the Scale and Reduce sampling mode. Does the solution meet the goal?

Options

• AYes
• BNo

Explanation

{"question_number": 8, "correct_answer": "B. No", "explanation": "'Scale and Reduce' is not a recognized sampling strategy for addressing class imbalance. It is not a feature of the Azure Machine Learning Studio sampling module designed for this purpose. To compensate for class imbalance, appropriate techniques include oversampling the minority class (e.g., SMOTE), undersampling the majority class, or using class weights. Since 'Scale and Reduce' does not address class imbalance, the solution does not meet the goal.", "generated_by": "claude-sonnet", "llm_judge_score": 4}

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