A decision boundary is a hypersurface that separates different classes in a classification problem. It represents the threshold at which the classifier decides between classes, effectively defining the region of input space where one class is predicted over another. Understanding decision boundaries is crucial in visualizing how algorithms like decision trees and random forests make their predictions based on input features.
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