Feature Selection Using Grey Wolf Optimization for Fetal Health Classification

Accurate categorization methods are crucial for expectant women to identify fetal health. This study utilized Grey Wolf Optimization (GWO) to perform Feature Selection, demonstrating its efficacy in preserving findings even when features are eliminated. In this research, GWO found the features, however the result is not satisfactory. The comparison of categorization results with and without GWO demonstrated consistent model performance. The Decision Tree model was the highest performing, attaining an accuracy, precision, recall, and F1-score of 0.93. These results emphasize the Grey Wolf Optimization (GWO) does not provide better feature selection.