A Decision Tree achieves 62% training accuracy and 60% test accuracy on a task where state-of-the-art is ~90%. The tree has max_depth=2 and min_samples_leaf=50. What is the most likely issue?

Question

Answer

The tree is underfitting — the constraints are too aggressive, preventing it from learning the data's complexity

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The tree is overfitting to the training set

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The dataset is too noisy for any classifier

Answer

Feature scaling was not applied

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A Decision Tree achieves 62% training accuracy and 60% test accuracy on a task w...

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