Research Of K-means Clustering Algorithm

Clustering is an important area for research in Data Mining, which is also an important method in data partition or data grouping. K-means algorithm is a traditional partition clustering method. It is widely used in the area of Data Mining to cluster large data sets due to its high efficiency. Based on the traditional clustering algorithms, we bring forward the WAC K-means algorithm based on the Weighted Ant Clustering. In this improved method a weighting idea is introduced to the ant algorithm and then the transition probability of ants is introduced into the K-means clustering algorithm to determine which group the data belongs to. Finally, apply the improved WAC K-means algorithm into the customer segmentation and application in Power Supply Enterprise. And it has realized the application of enterprise's customer segmentation and we could get valuable information.