Persistent K-Means: Stable Data Clustering Algorithm Based on K-Means Algorithm
نویسندگان
چکیده مقاله:
Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K-Means, which alters the convergence method of K-Means algorithm to provide more accurate clustering results than the K-means algorithm and its variants by increasing the clusters’ coherence. Persistent K-Means uses an iterative approach to discover the best result for consecutive iterations of K-Means algorithm.
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persistent k-means: stable data clustering algorithm based on k-means algorithm
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عنوان ژورنال
دوره 7 شماره 1
صفحات 57- 66
تاریخ انتشار 2014-02-01
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