Dynamic Clustering of Data with Modified K-Means Algorithm

Download Now
Provided by: International Association of Computer Science & Information Technology (IACSIT)
Topic: Data Management
Format: PDF
K-means is a widely used partitional clustering method. While there are considerable research efforts to characterize the key features of K-means clustering, further investigation is needed to reveal whether the optimal number of clusters can be found on the run based on the cluster quality measure. This paper presents a modified K-means algorithm with the intension of improving cluster quality and to fix the optimal number of cluster. The K-means algorithm takes number of clusters (K) as input from the user. But in the practical scenario, it is very difficult to fix the number of clusters in advance.
Download Now

Find By Topic