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Using the concept of overfitting, explain why when a model is fit to training data, zero error with those data is not necessarily good

Respuesta :

Kalahira
Having zero error does not allow for the complexity of real-world data to be introduced in the future. Having a perfect fit of the model could lead to data that shows some sort of a skew when another set of data is tested at some point in the future.