Feature interactions refer to the relationships between two or more features that can influence the outcome of a predictive model. Understanding these interactions is crucial because they can reveal hidden patterns and improve model accuracy by capturing the combined effects of features rather than evaluating them independently. Feature interactions can significantly enhance the predictive power of a model, making it essential to consider them during feature selection and engineering processes.
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