The overfitting
Example: Overfitting occurs when model learns noise instead of patterns
Definition
"The overfitting" refers to a situation in data science and machine learning where a model learns not only the underlying patterns but also the noise and random fluctuations in the training data, resulting in poor generalization to new, unseen data.
Etymology
The term "overfitting" originates from the field of statistics and machine learning. It combines 'over-', meaning excessively, and 'fitting,' which refers to how well a model matches data. Did you know? The concept highlights the risk of making a model too closely tailored to specific data, which ironically makes it less useful overall.
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"The overfitting" appears in the Vocaplus list "English - Data & AI - (A1-C2) - set 1", containing 110 commonly used words.
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