fuzzy decision trees

Fuzzy decision trees are a type of model used to make decisions or predictions that handle uncertainty and imprecision. Unlike traditional trees, where data points are strictly categorized, fuzzy trees allow data to belong to multiple categories simultaneously with varying degrees of confidence. This approach better reflects real-world situations where boundaries aren't clear-cut. For example, instead of saying a patient is definitively "high risk," a fuzzy tree might indicate they are "mostly high risk" with some uncertainty. This flexibility improves accuracy in complex, ambiguous scenarios by capturing nuanced patterns in data.