Overfitting Detection

Overfitting can be prevented by keeping the model small, fair distribution of training data, and sensibly set training parameters (number of data points, iterations, etc). This ensures the model doesn’t store extreme levels of detail of individual training samples.

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Explanation

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How it works

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How to implement