A Fuzzy Adaptive Binary Global Learning Colonization-MLP model for Body Fat Prediction

Body fat prediction is a step toward addressing obesity issues. In this paper, we propose a machine learning-based prediction model incorporating a novel fuzzy adaptive global learning binary colonization method for feature selection. Two fuzzy inference systems are used to select input features more purposefully. The proposed model is validated against several well-known feature selection-based models. Experimental results show that it is able to outperform the other models in comparison on most of the performance metrics considered.