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I understand that using cross validation we can validate our model, but it is also possible that maybe our model is underfitting; hence, providing wrong results. One possibility that I can think of
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a) Examples of underfitting, appropriate-fitting, and over-fitting
I tried a bunch of things: The dangers of unexpected overfitting
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