The Akaike Information Criterion (AIC) is a measure used in statistical model selection. It provides a means for assessing the relative quality of a set of statistical models for a given dataset. Named after the Japanese statistician Hirotugu Akaike, the AIC aims to find the model that best explains the data with the minimum number of parameters, thus avoiding overfitting.
