Akaike's information criterion, developed by
Hirotsugu Akaike under the name of "an information criterion" (AIC) in 1971 and proposed in Akaike (1974), is a measure of the goodness of fit of an estimated
statistical model. It is grounded in the concept of
entropy. The AIC is an operational way of trading off the complexity of an estimated model against how well the model fits the data.
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