Hybrid Gravitational Search and Particle Swarm Based Fuzzy MLP for Medical Data Classification

In this work, a hybrid training algorithm for fuzzy MLP, called Fuzzy MLP-GSPSO, has been proposed by combining two meta-heuristics: gravitational search (GS) and particle swarm optimization (PSO). The result model has been applied for classification of medical data. Five medical datasets from UCI machine learning repository are used as benchmark datasets for evaluating the performance of the proposed 'Fuzzy MLP-GSPSO' model. The experimental results show that Fuzzy MLP-GSPSO model outperforms Fuzzy MLP-GS and Fuzzy MLP-PSO for all the five datasets in terms of classification accuracy, and therefore can reduce overheads in medical diagnosis.