An Efficient Framework for Clustering Data Based on Dbscan and K-Means Algorithms
نویسندگان
چکیده
Abstarct— In this paper we have presented a proposed a three step framework,starting with finding the initial clusters and then initalizing initial cluster centers and finially partitioning data into most optimal clusters.we have employed some the most effiecient algorithms like Dbscan and K-Means(XK-Means) and we have tested our approach on iris data set. Keywords— exploratory vector;centroids;xk-means;euclidean distance;density rechable;Dbscan
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