Description
Overfitting in statistics is the act of mistaking noise for a signal. Overfitting makes a model look ββbetterββ on paper but perform ββworseββ in the real world. This may make it easier to get the model published in an academic journal or to sell to a client, crowding out more honest models from the marketplace. But if the model is fitting noise, it has the potential to hurt the science (quoted from Silver 2012 Penguin Press).
Reference: Silver 2012 Penguin Press
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