Anr An Algorithm To Recommend Initial Cluster Centers For K-means Algorithm
نویسندگان
چکیده
منابع مشابه
An Optimized k-means Algorithm for Selecting Initial Clustering Centers
Selecting the initial clustering centers randomly will cause an instability final result, and make it easy to fall into local minimum. To improve the shortcoming of the existing kmeans clustering center selection algorithm, an optimized k-means algorithm for selecting initial clustering centers is proposed in this paper. When the number of the sample’s maximum density parameter value is not uni...
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K means algorithm is most popular partition based algorithm that is widely used in data clustering. A Lot of algorithms have been proposed for data clustering using K-Means algorithm due to its simplicity, efficiency and ease convergence. In spite this K-Means algorithm has some drawbacks like initial cluster centers, stuck in local optima etc. In this study, a new method is proposed to address...
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The k-means algorithm is widely used in many applications due to its simplicity and fast speed. However, its result is very sensitive to the initialization step: choosing initial cluster centers. Different initialization algorithms may lead to different clustering results and may also affect the convergence of the method. In this paper, we propose a new algorithm for improving the initializatio...
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ژورنال
عنوان ژورنال: Journal of Mathematics and Computer Science
سال: 2014
ISSN: 2008-949X
DOI: 10.22436/jmcs.011.04.03