An Interval Slope Approach to Fuzzy C-Means Clustering Algorithm for Interval Valued Data
Yan Jin, Jiang Hong Ma · Advanced materials research · 2014
Interval data is a range of continuous values which can describe the uncertainty. The traditional clustering methods ignore the structure information of intervals. And some modified ones have been developed. We have already used Taylor technique to perform well in the fuzzy c-means clustering algorithm. In this paper, we propose a new way based on the mixed interval slopes technique and interval computing. Experimental results also show the effectiveness of our approach.