Intro to Scientific Computing
The Akaike Information Criterion (AIC) is a statistical measure used to compare the goodness of fit of different models while penalizing for the number of parameters in each model. It helps to identify the model that best explains the data without overfitting, balancing model complexity and accuracy. This criterion is especially relevant in non-linear curve fitting, where various models may be tested to find the most suitable one for the data at hand.
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