You’re testing your model and it is overly sensitive to the fluctuations of data and...

Overfitting occurs when a model learns not only the underlying patterns but also the noise in the training data, causing it to perform well on seen data but poorly on unseen data. The CPMAI™ Glossary defines overfitting as “a modeling error where a model learns the training data too well, including its noise, resulting in poor performance on new data.”

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