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* **"N"**: "N" could stand for **noise-related error**. This component might capture the extent to which your model is fitting the noise in the training data. A high "N" suggests that your model is overly complex and is overfitting the data. Reducing "N" would involve techniques like regularization, cross-validation, and simplifying the model architecture.
