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 ...

We propose a type-2 based clustering algorithm to capture data points and attributes relationship embedded in fuzzy subspaces. It is a modification of Gustafson Kessel clustering algorithm through deployment of type-2 fuzzy sets for high dimensional data. The experimental results have shown that type-2 projected GK algorithm perform considerably better than the comparative techniques. General T...

Fuzzy systems are capable to model the inherent uncertainties in real world problems and implement human decision making. In this paper two issues related to fuzzy systems development are addressed and solutions are proposed and implemented. First issue is related to the high dimensional data sets. Such kinds of data sets lead to explode the search space of generated rules and results into dete...

Mono-nuclear kernel function is presented in this paper based on the fuzzy c-means clustering algorithm for data clustering to do the improvement in the field of data mining, puts forward the fuzzy c-means clustering algorithm based on multiple kernel function (MKFCM) algorithm. Under fully unsupervised learning method, a set of Gaussian kernel function combination are assigned different weight...