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AI Concepts and TechniquesmediumMultiple ChoiceObjective-mapped

AI0-001 AI Concepts and Techniques Practice Question

A team is developing a sentiment analysis model and obtains the following performance on the test set: accuracy=0.92, precision=0.75, recall=0.80, F1=0.77. The baseline majority-class classifier achieves 0.85 accuracy. Which conclusion is MOST justified?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

The model likely suffers from class imbalance, as the gap between accuracy and precision suggests

Accuracy is high but precision and recall are notably lower, indicating class imbalance where the model biases toward the majority class, inflating accuracy.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • The model should use a different evaluation metric like BLEU

    Why it's wrong here

    BLEU is for text generation, not classification.

  • The model likely suffers from class imbalance, as the gap between accuracy and precision suggests

    Why this is correct

    High accuracy with lower precision/recall is a classic sign of imbalance; the model predicts majority class too often.

  • The model is excellent because accuracy is high

    Why it's wrong here

    Accuracy alone is insufficient; precision and recall tell a different story.

  • The model has high variance and is overfitting

    Why it's wrong here

    Overfitting would show high training accuracy but low test accuracy; here test accuracy is high.

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Senior Network & Security Engineer · founder of Courseiva

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