A dataset has significant label noise (many mislabelled examples). Comparing KNN with K=1 and a fully grown Decision Tree (no pruning), which analysis is correct?

Question

Answer

The Decision Tree will be robust because it considers global structure via information gain

Answer

The Decision Tree will perform worse because it cannot handle continuous features with noise

Answer

KNN with K=1 will be robust to noise because it looks at local structure

Answer

Both will perform poorly because both will memorise the noisy labels

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A dataset has significant label noise (many mislabelled examples). Comparing KNN...

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