Decision Trees often suffer from ______, where they perform well on training data but poorly on new, unseen data.

  • Overfitting
  • Pruning
  • Splitting
  • Underfitting
Decision Trees are prone to "Overfitting," where they become too complex and fit the training data too closely. This can lead to poor generalization to new, unseen data.
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