Improved FCM Algorithm for Clustering the IRIS Data
One of the most challenging analysis problems in the data mining domains is organizing large amounts of information. One approach to this problem is to cluster information based on the content of a collection of documents. In this paper, the authors present clustering method is very sensitive to the initial center values, requirements on the data set too high, and cannot handle noisy data the proposal method is using information entropy to initialize the cluster centers and introduce weighting parameters to adjust the location of cluster centers and noise problems. The improves clustering on web data efficiently using Fuzzy C-Means (FCM)clustering with iris data sets.