Why does overfilting occur in ML models?

Question

Options

• AThe training dataset does not reptesent all possible input values.
• BThe model contains a regularization method.
• CThe model training stops early because of an early stopping criterion.
• DThe training dataset contains too many features.

• A
  90% (35)
• B
  3% (1)
• C
  3% (1)
• D
  5% (2)

Explanation

Overfitting occurs when an ML model learns the training data too well, including noise and patterns that do not generalize to new data. A key cause of overfitting is when the training dataset does not represent all possible input values, leading the model to over-specialize on the limited data it was trained on, failing to generalize to unseen data. Overfitting often occurs when the training dataset is not representative of the broader population of possible inputs, causing the model to memorize specific patterns, including noise, rather than learning generalizable features.

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