Which of the following describes the situation when a model performs well on the training data but poorly on unseen data?

  • Bias
  • High Variance
  • Overfitting
  • Underfitting
This situation is known as overfitting, where a model learns to fit the training data too closely but fails to generalize to new, unseen data, resulting in a high error rate.
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