Clustering Algorithm In Data Mining Research

Data Mining is a superior area in the information and database technology, and is commonly considered as one of the key technology with wild developing perspective. Data Mining relates to statistics, AI, fuzzy theory, database technology etc, huge quantity data and retractile of algorithm are emphasized, it is also a technology approaching applied. Also it is difficult to realize.Clustering is an important area for research in Data Mining, and also an important method in data partition or data grouping. Clustering has been widely used in commerce, market analysis, biology, Web classification and so on.The paper summarizes and analyzes clustering technologies.First, the paper introduces main clustering algorithms systematically and analyzes the key techniques of clustering, second, two improved algorithms compared with the original ones are given. One is an improved algorithm of K-means which gives a new method of selecting initial centroids and the improved algorithm improves the clustering accuracy, the other is an improved algorithm of FCM. The basic idea of the algorithm is to modify the membership matrix and the optimal choice for parameter of number of c based on cluster validity function. Two improved algorithms are analyzed by experiments, and gets better results.