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

Answer

The tree is overfitting to the training set

Answer

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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