Data Science Numerical Analysis
AIC, or Akaike Information Criterion, is a measure used to compare different statistical models and to select the best one. It evaluates models based on the trade-off between goodness-of-fit and model complexity, penalizing for the number of parameters to avoid overfitting. A lower AIC value indicates a better model, balancing accuracy with simplicity.
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