Supervised fuzzy and Bayesian classification of high dimensional data: a comparative study
This paper presents a supervised fuzzy c-mean (SFCM) classifier for the classification of high dimensional data. The proposed SFCM classifier can be iterative or non iterative to reduce the computational time. Comparison with the conventional FCM clustering technique and the Bayesian classification technique is also presented. Performance results of the three algorithms are presented on simulated and real remote sensing multispectral data, which show improvement in the classification accuracy using the SFCM technique.