Fuzzy; BMI; VO2max

This paper presents a general methodological framework for constructing contextaware fuzzy partitions that extend conventional crisp categorizations. The approach is based on Nov´ak’s theory of fuzzy contexts and is implemented using the R package lfl. It enables smooth and interpretable transitions between adjacent classes while preserving the original categorical structure. To illustrate the procedure, we apply it to derive f itness-specific fuzzy partitions of Body Mass Index, where the conventional four categories (underweight, normal weight, overweight, obese) are adapted according to individual levels of cardiorespiratory fitness.

This paper presents a general methodological framework for constructing contextaware fuzzy partitions that extend conventional crisp categorizations. The approach is based on Nov´ak’s theory of fuzzy contexts and is implemented using the R package lfl. It enables smooth and interpretable transitions between adjacent classes while preserving the original categorical structure. To illustrate the procedure, we apply it to derive f itness-specific fuzzy partitions of Body Mass Index, where the conventional four categories (underweight, normal weight, overweight, obese) are adapted according to individual levels of cardiorespiratory fitness.