AIC (Akaike Information Criterion)

The Akaike Information Criterion (AIC) is a statistical tool used to compare different models that explain the same data. It helps identify the best model by balancing goodness of fit (how well the model explains the data) with complexity (the number of parameters in the model). A lower AIC value suggests a better model, meaning it explains the data well without being overly complicated. This is useful in research and data analysis, as it helps avoid overfitting while ensuring the model still captures essential patterns in the data.