Paper Info
Title
A Fast Iterative Algorithm for Identifying Feature Scales and Signed Fuzzy Measures in Generalized Choquet Integrals.
Abstract
We develop an iterative algorithm for identifying approximate optimal scales for feature attributes of generalized Choquet integrals. Based on the scales, the optimal values of fuzzy measures are also obtained immediately using least square method. The new algorithm is significantly faster than previous approaches using evolutionary computing. The experimental results produced by the iterative algorithm are also better than those from genetic algorithms.
Year
DOI
Venue
2005
10.1109/FUZZY.2005.1452373
IEEE International Conference on Fuzzy Systems
Keywords
Field
DocType
data mining,least square method,fuzzy set theory,parameter estimation,integral equations,evolutionary computing,iterative algorithm,iterative methods,genetic algorithms,predictive models,choquet integral,information science,mathematics,genetic algorithm,least squares approximation
Least squares,Iterative method,Computer science,Fuzzy measure theory,Fuzzy logic,Evolutionary computation,Integral equation,Fuzzy set,Artificial intelligence,Genetic algorithm,Machine learning
Conference
Citations 
PageRank 
References 
1
0.40
5
Authors
2
Name
Order
Citations
PageRank
Xutao Deng1868.22
Zhenyuan Wang268490.22