A KNN classifier with K=5 is trained on a dataset where 95% of samples belong to class A and 5% to class B. The model achieves 95% accuracy. A student claims the model is excellent. What is the best critique?

Question

Answer

K=5 is too small for imbalanced data and should be set to at least 50

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95% accuracy is always excellent regardless of class distribution

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The model may simply predict class A for everything; 95% accuracy matches the naive majority-class baseline, so the model may have learned nothing useful

Answer

KNN cannot handle imbalanced datasets at all

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A KNN classifier with K=5 is trained on a dataset where 95% of samples belong to...

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