Overfitting…

• DT is overfit when exists another DT’ and

  • DT has smaller error on training examples, but
  • DT has bigger error on test examples

• Causes of overfitting

  • Noisy data, or
  • Training set is too small

• Approaches

  • Stop before perfect tree, or
  • Postpruning

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