Overfitting

nounverified·updated Aug 28, 2026

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Given a hypothesis space H, a hypothesis h element of H is said to overfit the training data if there exists some alternative hypothesis h' element of H, such that h has smaller error than h' over the training examples, but h' has a smaller error than h over the entire distribution of instance.

Framework senses

2 senses across 2 frameworks

Machine Learning1 senseview framework →

§1: Given a hypothesis space H, a hypothesis h element of H is said to overfit the training data if there exists some alternative hypothesis h' element of H, such that h has smaller error than h' over the training examples, but h' has a smaller error than h over the entire distribution of instance.

Legacy lexicon import1 senseview framework →

§1 · legacy_primary: Given a hypothesis space H, a hypothesis h element of H is said to overfit the training data if there exists some alternative hypothesis h' element of H, such that h has smaller error than h' over the training examples, but h' has a smaller error than h over the entire distribution of instance.
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