Akaike Information Criterion (AIC)

The Akaike Information Criterion (AIC) is a tool statisticians use to select the best model among several options. It balances how well a model fits the data with its complexity—favoring simpler models that explain the data adequately to avoid overfitting. A lower AIC score indicates a better model because it suggests a good fit with fewer assumptions or parameters. Essentially, AIC helps identify the most efficient model that captures the key patterns in the data without unnecessary complexity.