An Empirical Comparison of Two Methods for Fuzzy Density

Information Fusion is a valid way which can decrease the uncertainty of making decision, and is also a hotspot. The paper makes some work on a important problem about Fuzzy Integral, that is how to get the Fuzzy Density, and compares two typical means. Based on 11 UCI data set, this paper conducts the compared experiment of several Information Fusion methods. It is compared with references 4 and 5. The result shows that the Fuzzy Integral method based on probability is better than the Fuzzy Integral method based on beliefs, is also better than the best results of single classifiers in references 4. The result also shows that the Fuzzy Integral method based on beliefs is nearly equal to the best results of fusion classifiers in references 5 in general, better than the average fusion method, and is also better the best results of single classifiers in references 4.