1. OverfittingIn statistics and machine learning, overfitting occurs when a statistical model describes random error or noise instead of the underlying relationship. Overfitting generally occurs when a model is excessively complex, such as having too many parameters relative to the number of observations. A model which has been overfit will generally have poor predictive performance, as it can exaggerate minor fluctuations in the data.
Read “Overfitting” on English Wikipedia
Read “過剰適合” on Japanese Wikipedia
Read “Overfitting” on DBpedia
Read “Overfitting” on English Wikipedia
Read “過剰適合” on Japanese Wikipedia
Read “Overfitting” on DBpedia
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