An Integrated Fuzzy Clustering Algorithm GFC for Switching Regressions

In order to solve switching regression problems, many approaches have been investigated. In this paper, an integrated fuzzy clustering algorithm GFC that combines gravity-based clustering algorithm GC with fuzzy clustering is presented. GC, as a new hard clustering algorithm presented here, is based on the well-known Newton’s Gravity Law. The theoretic analysis shows that GFC can converge to a local minimum of the object function. Experimental results show that GFC for switching regression problems has better performance than standard fuzzy clustering algorithms, especially in terms of convergence speed.